% This file was created with JabRef 2.9.2.
% Encoding: Cp1252
@ARTICLE{Herve2010PCA,
author = {Abdi, Herv\'{e} and Williams, Lynne J.},
title = {Principal component analysis},
journal = {Wiley Interdisciplinary Reviews: Computational Statistics},
year = {2010},
volume = {2},
pages = {433-459},
number = {4}
}
@BOOK{absil2009optimization,
title = {Optimization algorithms on matrix manifolds},
publisher = {Princeton University Press},
year = {2009},
author = {Absil, P-A and Mahony, Robert and Sepulchre, Rodolphe}
}
@ARTICLE{Alhaddad2012,
author = {Alhaddad, Mohammed J. and Kamel, Mahmoud and Malibary, Hussein and
Thabit, Khalid and Dahlwi, Foud and Hadi, Anas},
title = {P300 speller efficiency with common average reference},
journal = {Proceedings of the Third International conference on Autonomous and
Intelligent Systems},
year = {2012},
pages = {234-241},
numpages = {8}
}
@ARTICLE{Allison2010,
author = {B Z Allison and C Brunner and V Kaiser and G R Muller-Putz and C
Neuper and G Pfurtscheller},
title = {Toward a hybrid brain computer interface based on imagined movement
and visual attention},
journal = {Journal of Neural Engineering},
year = {2010},
volume = {7},
pages = {026007},
number = {2}
}
@INCOLLECTION{ALL10,
author = {Allison, Brendan Z. and Neuper, Christa},
title = {Could Anyone Use a {BCI}?},
booktitle = {Brain-Computer Interfaces},
publisher = {Springer London},
year = {2010},
editor = {Tan, Desney S. and Nijholt, Anton},
series = {Human-Computer Interaction Series},
chapter = {3},
pages = {35--54}
}
@ARTICLE{amari2010information,
author = {Amari, Shun-Ichi},
title = {Information geometry in optimization, machine learning and statistical
inference},
journal = {Frontiers of Electrical and Electronic Engineering in China},
year = {2010},
volume = {5},
pages = {241--260},
number = {3},
publisher = {Springer}
}
@ARTICLE{amari2009,
author = {Amari, S.-I.},
title = {$\alpha$-Divergence Is Unique, Belonging to Both $f$-Divergence and
{B}regman Divergence Classes},
journal = {Information Theory, IEEE Transactions on},
year = {2009},
volume = {55},
pages = {4925-4931},
number = {11},
doi = {10.1109/TIT.2009.2030485},
issn = {0018-9448},
keywords = {geometry;optimisation;statistical distributions;Bregman divergence;Fisher
metric;Kullback-Leibler divergence;alpha-divergence;f-divergence;geometrical
structure;information monotonicity;optimization problems;positive
arrays;probability distributions;Entropy;Information geometry;Matrix
decomposition;Physics;Probability distribution;$f$-divergence;Bregman
divergence;Fisher information;canonical divergence;dually flat structure;information
geometry;information monotonicity}
}
@ARTICLE{amari2009GSI,
author = {Amari, S.-I.},
title = {$\alpha$-Divergence Is Unique, Belonging to Both $f$-Divergence and
{B}regman Divergence Classes},
journal = {IEEE Trans Inf Theory},
year = {2009},
volume = {55},
pages = {4925-4931},
number = {11},
doi = {10.1109/TIT.2009.2030485},
issn = {0018-9448},
keywords = {geometry;optimisation;statistical distributions;Bregman divergence;Fisher
metric;Kullback-Leibler divergence;alpha-divergence;f-divergence;geometrical
structure;information monotonicity;optimization problems;positive
arrays;probability distributions;Entropy;Information geometry;Matrix
decomposition;Physics;Probability distribution;$f$-divergence;Bregman
divergence;Fisher information;canonical divergence;dually flat structure;information
geometry;information monotonicity},
owner = {Quentin},
timestamp = {2015.03.09}
}
@ARTICLE{KK.Ang2008FBCSP,
author = {Kai Keng Ang and Zhang Yang Chin and Haihong Zhang and Cuntai Guan},
title = {{Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface}},
journal = {Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational
Intelligence). IEEE International Joint Conference on},
year = {2008},
pages = {2390-2397}
}
@ARTICLE{KK.Ang2010Clinical,
author = {Kai Keng Ang and Cuntai Guan and Chua, K.S.G. and Beng Ti Ang and
Kuah, C. and Chuanchu Wang and Kok Soon Phua and Zheng Yang Chin
and Haihong Zhang},
title = {{Clinical study of neurorehabilitation in stroke using EEG-based
motor imagery brain-computer interface with robotic feedback}},
journal = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International
Conference of the IEEE},
year = {2010},
pages = {5549-5552}
}
@ARTICLE{ANG12,
author = {Ang, Kai Keng K. and Chin, Zheng Yang Y. and Wang, Chuanchu and Guan,
Cuntai and Zhang, Haihong},
title = {Filter Bank Common Spatial Pattern Algorithm on {BCI} Competition
{IV} Datasets 2a and 2b.},
journal = {Frontiers in neuroscience},
year = {2012},
volume = {6}
}
@ARTICLE{Arjona2011,
author = {Arjona, C. and Pentacolo, J. and Gareis, I. E. and Atum, Y. and Gentiletti,
G. and Acevedo, R. C. and Rufiner, H. L.},
title = {{Evaluation of LDA Ensembles Classifiers for Brain Computer Interface}},
journal = {Memorias del XVIII Congreso Argentino de Bioingenier\'{i}a (SABI
2011)},
year = {2011}
}
@ARTICLE{ARS07,
author = {Arsigny, Vincent and Fillard, Pierre and Pennec, Xavier and Ayache,
Nicholas},
title = {Geometric means in a novel vector space structure on symmetric positive-definite
matrices},
journal = {SIAM Journal on Matrix Analysis and Applications},
year = {2007},
volume = {29},
pages = {328--347},
number = {1},
publisher = {SIAM}
}
@ARTICLE{ARS06,
author = {Arsigny, Vincent and Fillard, Pierre and Pennec, Xavier and Ayache,
Nicholas},
title = {{Log-Euclidean} metrics for fast and simple calculus on diffusion
tensors},
journal = {Magn. Reson. Med.},
year = {2006},
volume = {56},
pages = {411--421},
number = {2}
}
@ARTICLE{Arvaneh2011,
author = {Arvaneh, M. and Cuntai Guan and Kai Keng Ang and Hiok Chai Quek},
title = {{Spatially sparsed Common Spatial Pattern to improve BCI performance}},
journal = {Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International
Conference on},
year = {2011},
pages = {2412-2415}
}
@ARTICLE{Bedard2006ModelOfLowPass,
author = {C B\'{e}dard and H Kr\"{o}ger and A Destexhe},
title = {Model of low-pass filtering of local field potentials in brain tissue},
journal = {Nonlinear Soft Matter Physics},
year = {2006},
volume = {73},
pages = {051911}
}
@INPROCEEDINGS{BAK08b,
author = {Baklouti, M. and Guyot, P. A. and Monacelli, E. and Couvet, S.},
title = {Force controlled upper-limb powered exoskeleton for rehabilitation},
booktitle = {Intelligent Robots and Systems (IROS)},
year = {2008},
pages = {4202},
abstract = {The goal of this project is to develop an upper limb exoskeletal orthosis
destinated to help disabled population to achieve arm movements.
This orthosis is principally designed for people suffering from myopathy
and muscle degeneration. Such patients cannot generate enough force
to move alone their arm. This poster presents a new approach to control
the exoskeleton using pressure sensors.}
}
@ARTICLE{Bamdadian2011,
author = {Bamdadian, A. and Cuntai Guan and Kai Keng Ang and Jianxin Xu},
title = {{Real coded GA-based SVM for motor imagery classification in a Brain-Computer
Interface}},
journal = {Control and Automation (ICCA), 2011 9th IEEE International Conference
on},
year = {2011},
pages = {1355-1359}
}
@INPROCEEDINGS{barachant2013riemannian,
author = {Barachant, Alexandre and Andreev, Anton and Congedo, Marco and others},
title = {The {R}iemannian Potato: an automatic and adaptive artifact detection
method for online experiments using {R}iemannian geometry},
booktitle = {Proceedings of TOBI Workshop IV},
year = {2013},
pages = {19--20}
}
@INPROCEEDINGS{barachant2011channel,
author = {Barachant, Alexandre and Bonnet, St{\'e}phane},
title = {Channel selection procedure using {R}iemannian distance for {BCI}
applications},
booktitle = {Neural Engineering (NER), 2011 5th International IEEE/EMBS Conference
on},
year = {2011},
pages = {348--351},
organization = {IEEE}
}
@ARTICLE{BAR13,
author = {Barachant, Alexandre and Bonnet, St\'{e}phane and Congedo, Marco
and Jutten, Christian},
title = {Classification of covariance matrices using a {R}iemannian-based
kernel for {BCI} applications},
journal = {Neurocomputing},
year = {2013},
volume = {112},
pages = {172--178}
}
@ARTICLE{barachant2012multiclass,
author = {Barachant, Alexandre and Bonnet, St{\'e}phane and Congedo, Marco
and Jutten, Christian},
title = {{Multiclass brain--computer interface classification by Riemannian
geometry}},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2012},
volume = {59},
pages = {920--928},
number = {4},
publisher = {IEEE}
}
@ARTICLE{barachant2012multiclassGSI,
author = {Barachant, Alexandre and Bonnet, St{\'e}phane and Congedo, Marco
and Jutten, Christian},
title = {{Multiclass brain--computer interface classification by Riemannian
geometry}},
journal = {IEEE Trans Biomed Eng},
year = {2012},
volume = {59},
pages = {920--928},
number = {4},
owner = {Quentin},
publisher = {IEEE},
timestamp = {2015.03.09}
}
@INPROCEEDINGS{barachant2010common,
author = {Barachant, Alexandre and Bonnet, St{\'e}phane and Congedo, Marco
and Jutten, Christian},
title = {Common spatial pattern revisited by {R}iemannian geometry},
booktitle = {Multimedia Signal Processing (MMSP), 2010 IEEE International Workshop
on},
year = {2010},
pages = {472--476},
organization = {IEEE}
}
@INCOLLECTION{barachant2010riemannian,
author = {Barachant, Alexandre and Bonnet, St{\'e}phane and Congedo, Marco
and Jutten, Christian},
title = {{R}iemannian geometry applied to {BCI} classification},
booktitle = {Latent Variable Analysis and Signal Separation},
publisher = {Springer},
year = {2010},
pages = {629--636}
}
@INPROCEEDINGS{barachant2012bci,
author = {Barachant, Alexandre and Bonnet, St{\'e}phane and Congedo, Marco
and Jutten, Christian and others},
title = {{BCI} Signal Classification using a Riemannian-based kernel},
booktitle = {Proceeding of the 20th European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning},
year = {2012},
pages = {97--102}
}
@ARTICLE{Bashashati2007,
author = {Bashashati, A. and Fatourechi, M and Ward, RK and Birch, GE},
title = {{A survey of signal processing algorithms in brain-computer interfaces
based on electrical brain signals}},
journal = {journal of neural engineering},
year = {2007},
volume = {4},
number = {2}
}
@ARTICLE{BAY00,
author = {Bayliss, Jessica D. and Ballard, Dana H.},
title = {Single trial P3 epoch recognition in a virtual environment},
journal = {Neurocomputing},
year = {2000},
volume = {32-33},
pages = {637--642}
}
@ARTICLE{Bayliss1998,
author = {Jessica D. Bayliss and Dana H. Ballard},
title = {{Single Trial P300 Recognition in a Virtual Environment}},
journal = {University of Rochester},
year = {1998},
pages = {22-25}
}
@BOOK{begg2007computational,
title = {Computational Intelligence in Biomedical Engineering},
publisher = {Taylor \& Francis},
year = {2007},
author = {Begg, R. and Lai, D.T.H. and Palaniswami, M.},
isbn = {9780849340802}
}
@ARTICLE{Bhattacharyya2010,
author = {Bhattacharyya, S. and Khasnobish, A. and Chatterjee, S. and Konar,
A. and Tibarewala, D.N.},
title = {{Performance analysis of LDA, QDA and KNN algorithms in left-right
limb movement classification from EEG data}},
journal = {Systems in Medicine and Biology (ICSMB), 2010 International Conference
on},
year = {2010},
pages = {126-131}
}
@ARTICLE{Bin2009AnOnlineMultiCh,
author = {Bin, G. and Gao, X. and Yan, Z. and Hong, B. and Gao, S.},
title = {{An online multi-channel SSVEP-based brain-computer interface using
a canonical correlation analysis method}},
journal = {Journal of Neural Engineering},
year = {2009},
volume = {6},
number = {4}
}
@ARTICLE{blankertz2011single,
author = {Blankertz, Benjamin and Lemm, Steven and Treder, Matthias and Haufe,
Stefan and M{\"u}ller, Klaus-Robert},
title = {Single-trial analysis and classification of {ERP} components: a tutorial},
journal = {NeuroImage},
year = {2011},
volume = {56},
pages = {814--825},
number = {2},
publisher = {Elsevier}
}
@ARTICLE{BLA04,
author = {Blankertz, Benjamin and M\"{u}ller, Klaus-Robert R. and Curio, Gabriel
and Vaughan, Theresa M. and Schalk, Gerwin and Wolpaw, Jonathan R.
and Schl\"{o}gl, Alois and Neuper, Christa and Pfurtscheller, Gert
and Hinterberger, Thilo and Schr\"{o}der, Michael and Birbaumer,
Niels},
title = {The {BCI} competition 2003: progress and perspectives in detection
and discrimination of {EEG} single trials},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2004},
volume = {51},
pages = {1044--1051},
number = {6},
abstract = {Interest in developing a new method of man-to-machine communication-a
brain-computer interface ({BCI})-has grown steadily over the past
few decades. {BCIs} create a new communication channel between the
brain and an output device by bypassing conventional motor output
pathways of nerves and muscles. These systems use signals recorded
from the scalp, the surface of the cortex, or from inside the brain
to enable users to control a variety of applications including simple
word-processing software and orthotics. {BCI} technology could therefore
provide a new communication and control option for individuals who
cannot otherwise express their wishes to the outside world. Signal
processing and classification methods are essential tools in the
development of improved {BCI} technology. We organized the {BCI}
Competition 2003 to evaluate the current state of the art of these
tools. Four laboratories well versed in {EEG}-based {BCI} research
provided six data sets in a documented format. We made these data
sets (i.e., labeled training sets and unlabeled test sets) and their
descriptions available on the Internet. The goal in the competition
was to maximize the performance measure for the test labels. Researchers
worldwide tested their algorithms and competed for the best classification
results. This paper describes the six data sets and the results and
function of the most successful algorithms.},
publisher = {IEEE}
}
@ARTICLE{Blankertz2006,
author = {Blankertz, B. and Muller, K.-R. and Krusienski, D.J. and Schalk,
G. and Wolpaw, J.R. and Schlogl, A. and Pfurtscheller, G. and Millan,
Jd.R. and Schroder, M. and Birbaumer, N.},
title = {{The BCI competition III: validating alternative approaches to actual
BCI problems}},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions
on},
year = {2006},
volume = {14},
pages = {153-159},
number = {2}
}
@ARTICLE{BLA06,
author = {Blankertz, B. and Muller, K. R. and Krusienski, D. J. and Schalk,
G. and Wolpaw, J. R. and Schlogl, A. and Pfurtscheller, G. and Millan,
Jd and Schroder, M. and Birbaumer, N.},
title = {The {BCI} competition {III}: validating alternative approaches to
actual {BCI} problems},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions
on},
year = {2006},
volume = {14},
pages = {153--159},
number = {2},
abstract = {A brain-computer interface ({BCI}) is a system that allows its users
to control external devices with brain activity. Although the proof-of-concept
was given decades ago, the reliable translation of user intent into
device control commands is still a major challenge. Success requires
the effective interaction of two adaptive controllers: the user's
brain, which produces brain activity that encodes intent, and the
{BCI} system, which translates that activity into device control
commands. In order to facilitate this interaction, many laboratories
are exploring a variety of signal analysis techniques to improve
the adaptation of the {BCI} system to the user. In the literature,
many machine learning and pattern classification algorithms have
been reported to give impressive results when applied to {BCI} data
in offline analyses. However, it is more difficult to evaluate their
relative value for actual online use. {BCI} data competitions have
been organized to provide objective formal evaluations of alternative
methods. Prompted by the great interest in the first two {BCI} Competitions,
we organized the third {BCI} Competition to address several of the
most difficult and important analysis problems in {BCI} research.
The paper describes the data sets that were provided to the competitors
and gives an overview of the results.},
booktitle = {Neural Systems and Rehabilitation Engineering, IEEE Transactions
on [see also IEEE Trans. on Rehabilitation Engineering]},
publisher = {IEEE}
}
@ARTICLE{Blankertz2002,
author = {Blankertz, Benjamin and Schaefer, Christin and Dornhege, Guido and
Curio, Gabriel},
title = {{Single Trial Detection of EEG Error Potentials: A Tool for Increasing
BCI Transmission Rates}},
journal = {Artificial Neural Networks ICANN 2002},
year = {2002},
volume = {2415},
pages = {1137-1143}
}
@INCOLLECTION{BLA08,
author = {Blankertz, Benjamin and Tangermann, Michael and Popescu, Florin and
Krauledat, Matthias and Fazli, Siamac and D\'{o}naczy, M\'{a}rton
and Curio, Gabriel and M\"{u}ller, Klaus-Robert},
title = {The Berlin {Brain-Computer} Interface},
booktitle = {Computational Intelligence: Research Frontiers},
publisher = {Springer Berlin Heidelberg},
year = {2008},
volume = {5050},
series = {Lecture Notes in Computer Science},
pages = {79--101},
abstract = {The Berlin {Brain-Computer} Interface ({BBCI}) uses a machine learning
approach to extract subject-specific patterns from high-dimensional
{EEG}-features optimized for revealing the user's mental state. Classical
{BCI} application are brain actuated tools for patients such as prostheses
(see Section 4.1) or mental text entry systems ([2] and see [3,4,5,6]
for an overview on {BCI}). In these applications the {BBCI} uses
natural motor competences of the users and specifically tailored
pattern recognition algorithms for detecting the user's intent. But
beyond rehabilitation, there is a wide range of possible applications
in which {BCI} technology is used to monitor other mental states,
often even covert ones (see also [7] in the {fMRI} realm). While
this field is still largely unexplored, two examples from our studies
are exemplified in Section 4.3 and 4.4.}
}
@ARTICLE{BLA08b,
author = {Blankertz, B. and Tomioka, R. and Lemm, S. and Kawanabe, M. and Muller,
K. R.},
title = {{Optimizing Spatial filters for Robust {EEG} {Single-Trial} Analysis}},
journal = {Signal Processing Magazine, IEEE},
year = {2008},
volume = {25},
pages = {41--56},
number = {1},
abstract = {Due to the volume conduction multichannel electroencephalogram ({EEG})
recordings give a rather blurred image of brain activity. Therefore
spatial filters are extremely useful in single-trial analysis in
order to improve the signal-to-noise ratio. There are powerful methods
from machine learning and signal processing that permit the optimization
of spatio-temporal filters for each subject in a data dependent fashion
beyond the fixed filters based on the sensor geometry, e.g., Laplacians.
Here we elucidate the theoretical background of the common spatial
pattern ({CSP}) algorithm, a popular method in brain-computer interface
({BCD} research. Apart from reviewing several variants of the basic
algorithm, we reveal tricks of the trade for achieving a powerful
{CSP} performance, briefly elaborate on theoretical aspects of {CSP},
and demonstrate the application of {CSP}-type preprocessing in our
studies of the Berlin {BCI} ({BBCI}) project.},
booktitle = {{Signal Processing Magazine, IEEE}},
publisher = {IEEE}
}
@ARTICLE{Brunner2007Spati,
author = {Clemens Brunner and Muhammad Naeem and Robert Leeb and Bernhard Graimann
and Gert Pfurtscheller},
title = {{Spatial filtering and selection of optimized components in four
class motor imagery EEG data using independent components analysis}},
journal = {Pattern Recognition Letters},
year = {2007},
volume = {28},
pages = {957-964},
number = {8}
}
@ARTICLE{Brunner2011,
author = {P Brunner and L Bianchi and C Guger and F Cincotti and G Schalk},
title = {{Current trends in hardware and software for brain-computer interfaces
(BCIs)}},
journal = {Journal of Neural Engineering},
year = {2011},
volume = {8},
pages = {025001},
number = {2}
}
@ARTICLE{Capilla2011SteadyState,
author = {Capilla, Almudena AND Pazo-Alvarez, Paula AND Darriba, Alvaro AND
Campo, Pablo AND Gross, Joachim},
title = {{Steady-State Visual Evoked Potentials Can Be Explained by Temporal
Superposition of Transient Event-Related Responses}},
journal = {PLoS ONE},
year = {2011},
volume = {6},
pages = {e14543},
number = {1}
}
@ARTICLE{Cecotti2011,
author = {Hubert Cecotti},
title = {{A time-frequency convolutional neural network for the offline classification
of steady-state visual evoked potential responses}},
journal = {Pattern Recognition Letters },
year = {2011},
volume = {32},
pages = {1145 - 1153},
number = {8}
}
@ARTICLE{cecotti2010selfpacessvep,
author = {Cecotti, H.},
title = {{A Self-Paced and Calibration-Less SSVEP-Based Brain Computer Interface
Speller}},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions
on},
year = {2010},
volume = {18},
pages = {127-133},
number = {2}
}
@ARTICLE{Cecotti2008,
author = {Cecotti, H. and Graeser, A.},
title = {{Convolutional Neural Network with embedded Fourier Transform for
EEG classification}},
journal = {Pattern Recognition, 2008. ICPR 2008. 19th International Conference
on},
year = {2008},
pages = {1-4}
}
@ELECTRONIC{ceremh,
author = {{CEREMH}},
title = {{Centre de Ressources \& d'Innovation Mobilit\'{e}({CEREMH})}},
url = {{http://www.ceremh.org/}}
}
@ARTICLE{CHAN11,
author = {Chang, Chih C. and Lin, Chih J.},
title = {{LIBSVM}: A Library for Support Vector Machines},
journal = {ACM Trans. Intell. Syst. Technol.},
year = {2011},
volume = {2},
number = {3},
publisher = {ACM}
}
@ARTICLE{Chang2011,
author = {Chang, Chih C. and Lin, Chih J.},
title = {{LIBSVM: A library for support vector machines}},
journal = {ACM Transactions on Intelligent Systems and Technology},
year = {2011},
volume = {2},
number = {3}
}
@INCOLLECTION{CHA11,
author = {Chaudhary, A. and Raheja, J.L. and Das, K. and Raheja, S.},
title = {A Survey on Hand Gesture Recognition in Context of Soft Computing
Advanced Computing},
booktitle = {Communications in Computer and Information Science},
year = {2011},
volume = {133},
pages = {46--55},
abstract = {Hand gestures recognition is the natural way of Human Machine interaction
and today many researchers in the academia and industry are interested
in this direction. It enables human being to interact with machine
very easily and conveniently without wearing any extra device. It
can be applied from sign language recognition to robot control and
from virtual reality to intelligent home systems. In this paper we
are discussing work done in the area of hand gesture recognition
where focus is on the soft computing based methods like artificial
neural network, fuzzy logic, genetic algorithms, etc. We also described
hand detection methods in the preprocessed image for detecting the
hand image. Most researchers used fingertips for hand detection in
appearance based modeling. Finally we are comparing results given
by different researchers after their implementation.}
}
@ARTICLE{CHE12,
author = {Chebbi, Zeineb and Moakher, Maher},
title = {Means of {H}ermitian positive-definite matrices based on the log-determinant
$\alpha$-divergence function},
journal = {Linear Algebra and its Applications},
year = {2012},
volume = {436},
pages = {1872--1889},
number = {7}
}
@ARTICLE{Chen2010,
author = {Cheng Chen and Wei Song and Jiacai Zhang and Zhiping Hu and He Xu},
title = {{An Adaptive Feature Extraction Method for Motor-Imagery BCI Systems}},
journal = {Computational Intelligence and Security (CIS), 2010 International
Conference on},
year = {2010},
pages = {275-279}
}
@INPROCEEDINGS{chen2012eeg,
author = {Chen, Chiu-Kuo and Chua, E and Hsieh, Zong-Han and Fang, Wai-Chi
and Wang, Yu-Te and Jung, Tzyy-Ping},
title = {An EEG-based brain?computer interface with real-time artifact removal
using independent component analysis},
booktitle = {Consumer Electronics-Berlin (ICCE-Berlin), 2012 IEEE International
Conference on},
year = {2012},
pages = {13--14},
organization = {IEEE}
}
@ARTICLE{Cheng2002Design,
author = {Ming Cheng and Xiaorong Gao and Shangkai Gao and Dingfeng Xu},
title = {Design and implementation of a brain-computer interface with high
transfer rates},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2002},
volume = {49},
pages = {1181-1186},
number = {10}
}
@ARTICLE{Cincotti2010,
author = {Cincotti, F. and Scipione, A. and Timperi, A. and Mattia, D. and
Marciani, A.G. and Millan, J. and Salinari, S. and Bianchi, L. and
Bablioni, F.},
title = {Comparison of different feature classifiers for brain computer interfaces},
journal = {Neural Engineering, 2003. Conference Proceedings. First International
IEEE EMBS Conference on},
year = {2003},
pages = {645-647}
}
@ARTICLE{cohen1960,
author = {Cohen, J.},
title = {{A Coefficient of Agreement for Nominal Scales}},
journal = {Educational and Psychological Measurement},
year = {1960},
volume = {20},
pages = {37},
number = {1}
}
@ARTICLE{Comon1994ICA,
author = {Comon, Pierre},
title = {{Independent component analysis, a new concept?}},
journal = {Signal Process.},
year = {1994},
volume = {36},
pages = {287-314},
number = {3}
}
@ARTICLE{congedo2013new,
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year = {2013}
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Muller and F. Popescu},
title = {{Ensembles of temporal filters enhance classification performance
for ERD-based BCI systems}},
journal = {Proceedings of the 4th International Brain-Computer Interface Workshop
and Training Course},
year = {2008}
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title = {{Error-Related EEG Potentials Generated During Simulated Brain-Computer
Interaction}},
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author = {Ferrez, P. W. and Millan, J. del R.},
title = {{Simultaneous Real-Time Detection of Motor Imagery and Error-Related
Potentials for Improved BCI Accuracy}},
journal = {Proceedings of the 4th International Brain-Computer Interface Workshop
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series = {LNCS},
pages = {87--98}
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Interfaces for Continuous Control of Robots}},
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author = {Goh, Alvina and Vidal, Ren{\'e}},
title = {{Clustering and dimensionality reduction on Riemannian manifolds}},
booktitle = {{Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference
on}},
year = {2008},
pages = {1--7},
organization = {IEEE}
}
@INPROCEEDINGS{goh2008unsupervised,
author = {Goh, Alvina and Vidal, Ren{\'e}},
title = {{Unsupervised Riemannian clustering of probability density functions}},
booktitle = {{Machine Learning and Knowledge Discovery in Databases}},
year = {2008},
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publisher = {Springer}
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on},
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Pfurtscheller, G.}},
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Strein, T. and Pfurtscheller, G.},
title = {{Rapid prototyping of an EEG-based brain-computer interface (BCI)}},
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on},
year = {2001},
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number = {1}
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author = {Hammer, Eva M. and Halder, Sebastian and Blankertz, Benjamin and
Sannelli, Claudia and Dickhaus, Thorsten and Kleih, Sonja and M{\"u}ller,
Klaus-Robert and K{\"u}bler, Andrea},
title = {{Psychological predictors of {SMR}-{BCI} performance}},
journal = {Biological Psychology},
year = {2012},
volume = {89},
pages = {80--86},
number = {1},
abstract = {After about 30 years of research on {Brain-Computer} Interfaces ({BCIs})
there is little knowledge about the phenomenon, that some people
- healthy as well as individuals with disease -- are not able to
learn {BCI}-control. To elucidate this " {BCI}-inefficiency" phenomenon,
the current study investigated whether psychological parameters,
such as attention span, personality or motivation, could predict
performance in a single session with a {BCI} controlled by modulation
of sensorimotor rhythms ({SMR}) with motor imagery. A total of N
= 83 healthy {BCI} novices took part in the session. Psychological
parameters were measured with an electronic test-battery including
clinical, personality and performance tests. Predictors were determined
by binary logistic regression analyses. The output variable of the
{Two-Hand} Coordination Test ({2HAND}) \" overall mean error duration\"
which is a measure for the accuracy of fine motor skills accounted
for 11\% of the variance in {BCI}-inefficiency. The Attitudes Towards
Work ({AHA}) test variable \"performance level\" which can be interpreted
as a degree of concentration and a neurophysiological {SMR} predictor
were also identified as significant predictors of {SMR} {BCI} performance.
Psychological parameters as measured in this study play a moderate
role for one-session performance in a {BCI} controlled by modulation
of {SMR}. Fine motor skills predict {SMR}-{BCI} performance. The
amount of concentration predicts {SMR}-{BCI} performance. Biological,
psychological and physiological factors lead to an explanation of
30\% of the variance in {SMR}-{BCI} performance.}
}
@ARTICLE{Hardoon2004,
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title = {{Classifying EEG and ECoG Signals without Subject Training for Fast
BCI Implementation: Comparison of Non-Paralysed and Completely Paralysed
Subjects}},
journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
year = {2006},
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number = {2}
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@ELECTRONIC{openvibe,
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}
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Li, Hongdong and Harandi, Mehrtash},
title = {Kernel methods on the {R}iemannian manifold of symmetric positive
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booktitle = {Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference
on},
year = {2013},
pages = {73--80},
organization = {IEEE}
}
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title = {{Frequency and Phase Mixed Coding in SSVEP-Based Brain--Computer
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publisher = {Springer},
year = {2011},
author = {Jost, J{\"u}rgen},
volume = {62011}
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@ARTICLE{JRA11,
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R. and Yger, F. and Rakotomamonjy, A.},
title = {{sw-SVM}: sensor weighting support vector machines for {EEG}-based
brain--computer interfaces},
journal = {Journal of Neural Engineering},
year = {2011},
volume = {8},
pages = {056004+}
}
@ARTICLE{Jrad2011,
author = {N Jrad and M Congedo and R Phlypo and S Rousseau and R Flamary and
F Yger and A Rakotomamonjy},
title = {{sw-SVM: sensor weighting support vector machines for EEG-based brain-computer
interfaces}},
journal = {Journal of Neural Engineering},
year = {2011},
volume = {8},
pages = {056004},
number = {5}
}
@INPROCEEDINGS{kalunga2013ssvep,
author = {Kalunga, Emmanuel and Djouani, Karim and Hamam, Yskandar and Chevallier,
Sylvain and Monacelli, Eric},
title = {{SSVEP enhancement based on Canonical Correlation Analysis to improve
BCI performances}},
booktitle = {AFRICON, 2013},
year = {2013},
pages = {1--5},
organization = {IEEE}
}
@TECHREPORT{KAL15,
author = {Kalunga, Emmanuel K. and Chevallier, Sylvain and Barth\'elemy, Quentin},
title = {Using Riemannian geometry for {SSVEP}-based Brain Computer Interface},
institution = {Tshwane University of Technology \& Universit\'e de Versailles Saint-Quentin},
year = {2015},
archiveprefix = {arXiv},
url = {http://arxiv.org/abs/1501.03227}
}
@INPROCEEDINGS{kalunga2014hybrid,
author = {Kalunga, Emmanuel K. and Chevallier, Sylvain and Rabreau, Olivier
and Monacelli, Eric},
title = {{Hybrid interface: Integrating BCI in multimodal human-machine interfaces}},
booktitle = {Advanced Intelligent Mechatronics (AIM), 2014 IEEE/ASME Int. Conf.
on},
year = {2014},
pages = {530--535},
organization = {IEEE},
citeulike-article-id = {13492921},
keywords = {bcihybrid, bvi, ethicomp2015},
posted-at = {2015-01-16 03:05:23},
priority = {2}
}
@ARTICLE{Kaper2004,
author = {Kaper, M. and Meinicke, P. and Grossekathoefer, U. and Lingner, T.
and Ritter, H.},
title = {{BCI competition 2003-data set IIb: support vector machines for the
P300 speller paradigm}},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2004},
volume = {51},
pages = {1073-1076},
number = {6}
}
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title = {EEG signal classification for real-time brain-computer interface
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journal = {Mechatronics (ICOM), 2011 4th International Conference On},
year = {2011},
pages = {1-7}
}
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@ARTICLE{Krusienski2008,
author = {Krusienski, Dean J. and Sellers, Eric W. and McFarland, Dennis J.
and Vaughan, Theresa M. and Wolpaw, Jonathan R.},
title = {{Toward Enhanced P300 Speller Performance}},
journal = {Journal of Neuroscience Methods},
year = {2008},
volume = {167},
pages = {15-21},
number = {1}
}
@ARTICLE{Kumar2010Design,
author = {Kumar, A. and Mohanty, M.N. and Routray, A.},
title = {{Design of Support Vector Machines with Time Frequency Kernels for
classification of EEG signals}},
journal = {Students' Technology Symposium (TechSym), 2010 IEEE},
year = {2010},
pages = {330-333}
}
@ARTICLE{Lalor2005,
author = {Lalor, E. C. and Kelly, S. P. and Finucane, C. and Burke, R. and
Smith, R. and Reilly, R. B. and McDarby, G.},
title = {{Steady-state VEP-based brain-computer interface control in an immersive
3D gaming environment}},
journal = {EURASIP Journal on Applied Signal Processing},
year = {2005},
volume = {2005},
pages = {3156-3164},
numpages = {9}
}
@INCOLLECTION{Lao2013,
author = {Lao, KaFai and Wong, ChiMan and Wan, Feng and Mak, PuiIn and Mak,
PengUn and Vai, MangI},
title = {Canonical Correlation Analysis Neural Network for {Steady-State}
Visual Evoked Potentials Based {Brain-Computer} Interfaces},
booktitle = {Advances in Neural Networks - ISNN 2013},
publisher = {Springer},
year = {2013},
editor = {Guo, Chengan and Hou, Zeng-Guang and Zeng, Zhigang},
volume = {7952},
series = {Lecture Notes in Computer Science},
pages = {276--283}
}
@ARTICLE{ledoit2004well,
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title = {A well-conditioned estimator for large-dimensional covariance matrices},
journal = {Journal of multivariate analysis},
year = {2004},
volume = {88},
pages = {365--411},
number = {2},
publisher = {Elsevier}
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@ARTICLE{Lee2003,
author = {Hyekyung Lee and Seungjin Choi},
title = {{PCA+HMM+SVM for EEG pattern classification}},
journal = {Signal Processing and Its Applications, 2003. Proceedings. Seventh
International Symposium on},
year = {2003},
volume = {1},
pages = { 541-544}
}
@ARTICLE{Lee2002,
author = {Lee, Hyekyoung and Choi, Seungjin},
title = {{PCA-based linear dynamical systems for multichannel EEG classification}},
journal = {Neural Information Processing, 2002. ICONIP '02. Proceedings of the
9th International Conference on},
year = {2002},
volume = {2},
pages = { 745-749}
}
@BOOK{lee2010introduction,
title = {Introduction to topological manifolds},
publisher = {Springer},
year = {2010},
author = {Lee, John},
volume = {940}
}
@ARTICLE{Leeb2010,
author = {Leeb, R. and Sagha, H. and Chavarriaga, R. and del R Millan, J.},
title = {{Multimodal Fusion of Muscle and Brain Signals for a Hybrid-BCI}},
journal = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International
Conference of the IEEE},
year = {2010},
pages = {4343-4346}
}
@ARTICLE{Legeny2013,
author = {Legeny, J. and Viciana-Abad, R. and L{\'e}cuyer, A.},
title = {Toward Contextual SSVEP-Based BCI Controller: Smart Activation of
Stimuli and Control Weighting},
journal = {Computational Intelligence and AI in Games, IEEE Transactions on},
year = {2013},
volume = {5},
pages = {111-116},
number = {2},
month = {June}
}
@ARTICLE{Lei2009,
author = {Xu Lei and Ping Yang and Peng Xu and Tie-Jun Liu and De-Zhong Yao},
title = {{Common Spatial Pattern Ensemble Classifier and its Application in
Brain-Computer Interface}},
journal = {Journal of electronic science and technology of China},
year = {2009},
volume = {7},
number = {1}
}
@ARTICLE{Lemm2004,
author = {Lemm, S. and Schafer, C. and Curio, G.},
title = {{BCI competition 2003-data set III: probabilistic modeling of sensorimotor
mu; rhythms for classification of imaginary hand movements}},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2004},
volume = {51},
pages = {1077-1080},
number = {6}
}
@ARTICLE{Lenhardt2008,
author = {Lenhardt, A. and Kaper, M. and Ritter, H.J.},
title = {{An Adaptive P300-Based Online Brain Computer Interface}},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions
on},
year = {2008},
volume = {16},
pages = {121-130},
number = {2}
}
@ARTICLE{Li2011Multi-class,
author = {Mingai Li and Lin Lin and Songmin Jia},
title = {{Multi-class imagery EEG recognition based on adaptive subject-based
feature extraction and SVM-BP classifier}},
journal = {Mechatronics and Automation (ICMA), 2011 International Conference
on},
year = {2011},
pages = {1184-1189}
}
@ARTICLE{li2012electroencephalogram,
author = {Li, Y and Wong, KM and De Bruin, H},
title = {Electroencephalogram signals classification for sleepstate decision:
A {R}iemannian geometry approach},
journal = {Signal Processing, IET},
year = {2012},
volume = {6},
pages = {288--299},
number = {4},
publisher = {IET}
}
@ARTICLE{LI13,
author = {Li, Yili and Wong, K. M.},
title = {Riemannian Distances for Signal Classification by Power Spectral
Density},
journal = {Selected Topics in Signal Processing, IEEE Journal of},
year = {2013},
volume = {7},
pages = {655--669},
number = {4},
publisher = {IEEE}
}
@INPROCEEDINGS{li2009eeg,
author = {Li, Yili and Wong, Kon Max and De Bruin, H},
title = {{EEG} signal classification based on a {R}iemannian distance measure},
booktitle = {Science and Technology for Humanity (TIC-STH), 2009 IEEE Toronto
International Conference},
year = {2009},
pages = {268--273},
organization = {IEEE}
}
@ARTICLE{Lin2007,
author = {Zhonglin Lin and Changshui Zhang and Wei Wu and Xiaorong Gao},
title = {{Frequency Recognition Based on Canonical Correlation Analysis for
SSVEP-Based BCIs}},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2006},
volume = {53},
pages = {2610-2614},
number = {12}
}
@ARTICLE{Liu2011Novel,
author = {Yi Hung Liu and Ching An Cheng and Han-Pang Huang},
title = {Novel feature of the {EEG} based motor imagery {BCI} system: Degree
of imagery},
journal = {System Science and Engineering (ICSSE), 2011 International Conference
on},
year = {2011},
pages = {515-520}
}
@ARTICLE{LOP09,
author = {Lopez, M. A. and Pomares, Hector and Pelayo, Francisco and Urquiza,
Jose and Perez, Javier},
title = {Evidences of cognitive effects over auditory steady-state responses
by means of artificial neural networks and its use in brain--computer
interfaces},
journal = {Neurocomputing},
year = {2009},
volume = {72},
pages = {3617--3623},
number = {16-18}
}
@ARTICLE{Lopez-Gordo2010,
author = {Lopez-Gordo, M.A. and Pelayo, F. and Prieto, A.},
title = {{A high performance SSVEP-BCI without gazing}},
journal = {Neural Networks (IJCNN), The 2010 International Joint Conference
on},
year = {2010},
pages = {1-5}
}
@ARTICLE{Lotte2007Review,
author = {Lotte, F. and Congedo, M. and L\'{e}cuyer, A. and Lamarche, F. and
Arnaldi, B.},
title = {{A review of classification algorithms for EEG-based brain-computer
interfaces.}},
journal = {Journal of Neural Engineering},
year = {2007},
volume = {4},
pages = {R1},
number = {2}
}
@ARTICLE{LOT11,
author = {Lotte, F. and Guan, Cuntai},
title = {{Regularizing Common Spatial Patterns to Improve {BCI} Designs: Unified
Theory and New Algorithms}},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2011},
volume = {58},
pages = {355--362},
number = {2}
}
@ARTICLE{Lotte2008,
author = {Lotte, Fabien and Mouch\`{e}re, Harold and L\'{e}cuyer, Anatole},
title = {{Pattern rejection strategies for the design of self-paced EEG-based
Brain-Computer Interfaces.}},
journal = {ICPR},
year = {2008},
pages = {1-5},
publisher = {IEEE}
}
@ARTICLE{lotte2010exploring,
author = {Lotte, Fabien and Van Langhenhove, Aur{\'e}lien and Lamarche, Fabrice
and Ernest, Thomas and Renard, Yann and Arnaldi, Bruno and L{\'e}cuyer,
Anatole},
title = {Exploring large virtual environments by thoughts using a brain-computer
interface based on motor imagery and high-level commands},
journal = {Presence: teleoperators and virtual environments},
year = {2010},
volume = {19},
pages = {54--70},
number = {1}
}
@ARTICLE{Lu2010Regular,
author = {Haiping Lu and How-Lung Eng and Cuntai Guan and Plataniotis, K.N.
and Venetsanopoulos, A.N.},
title = {{Regularized Common Spatial Pattern With Aggregation for EEG Classification
in Small-Sample Setting}},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2010},
volume = {57},
pages = {2936-2946},
number = {12}
}
@ARTICLE{Muller2004machinelearning,
author = {K.R. M\"{u}ller and M. Krauledat and G. Dornhege and G. Curio and
B. Blankertz},
title = {Machine learning techniques for brain-computer interfaces},
journal = {Biomedical Engineering},
year = {2004},
pages = {11-22}
}
@ARTICLE{Ma2011,
author = {Xin Ma},
title = {{The research of brain-computer interface based on AAR parameters
and neural networks classifier}},
journal = {Computer Science and Network Technology (ICCSNT), 2011 International
Conference on},
year = {2011},
volume = {4},
pages = {2561-2564}
}
@ARTICLE{Manoochehri2011,
author = {Manoochehri, M. and Moradi, M.H.},
title = {{The new post processing method for self-paced BCI system}},
journal = {Biomedical Engineering (ICBME), 2011 18th Iranian Conference of},
year = {2011},
pages = {152-155}
}
@INPROCEEDINGS{CHE12a,
author = {Martin, Hugo and Chevallier, Sylvain and Monacelli, Eric},
title = {{Fast calibration of hand movement-based interface for arm exoskeleton
control}},
booktitle = {{European Symposium on Artificial Neural Networks (ESANN)}},
year = {2012},
pages = {573--578},
abstract = {Several muscular degenerative diseases alter motor abilities of large
muscles but spare smaller muscles, e.g. keeping hand motor skills
relatively unaffected while upper limbs ones are altered. Thus, hand
movements could be be used to control an arm exoskeleton for rehabilitation
and assistive purpose. Using an infra-red sensors (IR) based interface
for the exoskeleton control, this paper describes the learning part
of the system, endowing the system with a fast online calibration
and adaptation abilities. This learning component shows good results
and have been successfully implemented on the real system.}
}
@ARTICLE{McFarland2006,
author = {McFarland, D.J. and Anderson, C.W. and Muller, K.R. and Schlogl,
A. and Krusienski, D.J.},
title = {{BCI} meeting 2005-workshop on {BCI} signal processing: feature extraction
and translation},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions
on},
year = {2006},
volume = {14},
pages = {135-138},
number = {2}
}
@ARTICLE{McFarland1997El,
author = {McFarland, D. and McCane, L. and David, S. and Wolpaw, J.},
title = {{Spatial filter selection for EEG-based communication}},
journal = {Electroencephalography and Clinical Neurophysiology},
year = {1997},
volume = {103},
pages = {386--394},
number = {3}
}
@ARTICLE{McFarland1997,
author = {Dennis J. McFarland and Lynn M. McCane and Stephen V. David and Jonathan
R. Wolpaw},
title = {{Spatial filter selection for EEG-based communication}},
journal = {Electroencephalography and Clinical Neurophysiology},
year = {1997},
volume = {103},
pages = {386-394},
number = {3}
}
@ARTICLE{Millan2010,
author = {Mill\'{a}n, Jos\'{e} del R. and Rupp, Rudiger and Mueller-Putz, Gernot
and Murray-Smith, Roderick and Giugliemma, Claudio and Tangermann,
Michael and Vidaurre, Carmen and Cincotti, Febo and Kubler, Andrea
and Leeb, Robert and Neuper, Christa and Mueller, Klaus R and Mattia,
Donatella},
title = {{Combining Brain-Computer Interfaces and Assistive Technologies:
State-of-the-Art and Challenges}},
journal = {Frontiers in Neuroscience},
year = {2010},
volume = {4},
number = {161}
}
@ARTICLE{Millan2009,
author = {Millan, J.d.R. and Galan, F. and Vanhooydonck, D. and Lew, E. and
Philips, J. and Nuttin, M.},
title = {Asynchronous non-invasive brain-actuated control of an intelligent
wheelchair},
journal = {Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual
International Conference of the IEEE},
year = {2009},
pages = {3361-3364}
}
@ARTICLE{Millan2004noninvasivebrain,
author = {Jose Del R. Millan and Frederic Renkens and Josep Mourino and Wulfram
Gerstner},
title = {{Noninvasive brain-actuated control of a mobile robot by human EEG}},
journal = {IEEE Transactions on Biomedical Engineering},
year = {2004},
volume = {51},
pages = {1026-1033}
}
@ARTICLE{Ming2012,
author = {Dong Ming and Changcheng Sun and Longlong Cheng and Yanru Bai and
Xiuyun Liu and Xingwei An and Hongzhi Qi and Baikun Wan and Yong
Hu and Luk, K.D.K.},
title = {{ICA-SVM combination algorithm for identification of motor imagery
potentials}},
journal = {Computational Intelligence for Measurement Systems and Applications
(CIMSA), 2010 IEEE International Conference on},
year = {2010},
pages = {92-96}
}
@ARTICLE{moakher2005differential,
author = {Moakher, Maher},
title = {A differential geometric approach to the geometric mean of symmetric
positive-definite matrices},
journal = {SIAM Journal on Matrix Analysis and Applications},
year = {2005},
volume = {26},
pages = {735--747},
number = {3},
publisher = {SIAM}
}
@ARTICLE{Mohamed2011,
author = {Mohamed, A.K. and Marwala, T. and John, L.R.},
title = {{Single-trial EEG discrimination between wrist and finger movement
imagery and execution in a sensorimotor BCI}},
journal = {Engineering in Medicine and Biology Society,EMBC, 2011 Annual International
Conference of the IEEE},
year = {2011},
pages = {6289-6293}
}
@ARTICLE{movahedi2013development,
author = {Movahedi, MM and Mehdizadeh, AR and Alipour, A},
title = {Development of a Brain Computer Interface (BCI) Speller System Based
on SSVEP Signals},
journal = {Journal of Biomedical Physics and Engineering},
year = {2013},
volume = {3},
number = {3 Sep}
}
@ARTICLE{Mueller-Putz2008,
author = {Mueller-Putz, Gernot and Scherer, Reinhold and Brunner, Clemens and
Leeb, Robert and Pfurtscheller, Gert},
title = {Better than random: {A} closer look on {BCI} results.},
journal = {International Journal of Bioelectromagnetism},
year = {2008},
volume = {10},
pages = {52-55},
number = {1}
}
@ARTICLE{Muller-Putz2008ControlOfAnElec,
author = {Muller-Putz, Gernot R. and Pfurtscheller, Gert},
title = {{Control of an Electrical Prosthesis With an SSVEP-Based BCI}},
journal = {IEEE Transactions on Biomedical Engineering},
year = {2008},
volume = {55},
pages = {361-364},
number = {1}
}
@ARTICLE{Neuper1999,
author = {Neuper, C. and Pfurtscheller, G. and Schlogl, A. },
title = {{Enhancement of left-right sensorimotor EEG differences during feedback-regulated
motor imagery}},
journal = {Clinical Neurology},
year = {1999},
volume = {16},
pages = {373-382},
number = {4}
}
@ARTICLE{NicolasAlonso2012,
author = {Nicolas-Alonso and Luis Fernando and Gomez-Gil, Jaime},
title = {{Brain Computer Interfaces, a Review}},
journal = {Sensors},
year = {2012},
volume = {12},
pages = {1211-1279},
number = {2}
}
@BOOK{NIE04,
title = {Electroencephalography: Basic Principles, Clinical Applications,
and Related Fields},
publisher = {Lippincott Williams \& Wilkins},
year = {2004},
author = {Niedermeyer, E. and Lopes da Silva, F.},
edition = {5th}
}
@BOOK{Niedermeyer2004,
title = {Electroencephalography: Basic Principles, Clinical Applications,
and Related Fields},
publisher = {Lippincott Williams \& Wilkins},
year = {2004},
author = {Niedermeyer, Ernst and da Silva, Fernando L.},
edition = {5th},
isbn = {0781751268}
}
@BOOK{NIE12,
title = {Matrix Information Geometry},
publisher = {Springer Publishing Company, Incorporated},
year = {2012},
author = {Nielsen, Frank and Bhatia, Rajendra}
}
@BOOK{Nunez2005ElectricFieldsOfTheBrain,
title = {{Electric Fields of the Brain: The Neurophysics of EEG, 2nd Edition}},
publisher = {Oxford University Press, USA},
year = {2005},
author = {Nunez, Paul L. and Srinivasan, Ramesh},
edition = {2},
isbn = {019505038X}
}
@ARTICLE{Obermaier2001,
author = {B Obermaier and C Guger and C Neuper and G Pfurtscheller},
title = {{Hidden Markov models for online classification of single trial EEG
data}},
journal = {Pattern Recognition Letters},
year = {2001},
volume = {22},
pages = {1299-1309},
number = {12}
}
@ARTICLE{Ozmen2011Discrim,
author = {Ozmen, N.G. and Ktu, L.G.},
title = {{Discrimination between mental and motor tasks of EEG signals using
different classification methods}},
journal = {Innovations in Intelligent Systems and Applications (INISTA), 2011
International Symposium on},
year = {2011},
pages = {143-147}
}
@ARTICLE{Palaniappan2000,
author = {Palaniappan, R. and Raveendran, P. and Nishida, S. and Saiwaki, N.},
title = {{Autoregressive spectral analysis and model order selection criteria
for EEG signals}},
journal = {TENCON 2000. Proceedings},
year = {2000},
volume = {2},
pages = {126-129}
}
@ARTICLE{Pan2011,
author = {Pan, Jie and Gao, Xiaorong and Duan, Fang and Yan, Zheng and Gao,
Shangkai},
title = {Enhancing the classification accuracy of steady-state visual evoked
potential-based brain-computer interfaces using phase constrained
canonical correlation analysis},
journal = {Journal of neural engineering},
year = {2011},
volume = {8},
pages = {036027},
number = {3}
}
@ARTICLE{panicker2010adaptation,
author = {Panicker, Rajesh C and Puthusserypady, Sadasivan and Sun, Ying},
title = {Adaptation in P300 brain--computer interfaces: A two-classifier cotraining
approach},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2010},
volume = {57},
pages = {2927--2935},
number = {12},
publisher = {IEEE}
}
@INPROCEEDINGS{pascal123theoretical,
author = {Pascal, F. and Forster, P. and Ovarlez, J. -P and Arzabal, P.},
title = {Theoretical analysis of an improved covariance matrix estimator in
non-Gaussian noise},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing
(ICASSP). },
year = {2005},
volume = {4},
month = {March}
}
@ARTICLE{Pastor2003Human,
author = {Pastor, Maria A.},
title = {Human cerebral activation during steady-state visual-evoked responses},
journal = {The Journal of Neuroscience},
year = {2003},
volume = {23},
pages = {11621-11627},
number = {37}
}
@ARTICLE{pencina2008evaluating,
author = {Pencina, Michael J and D'Agostino, Ralph B and Vasan, Ramachandran
S},
title = {Evaluating the added predictive ability of a new marker: from area
under the {ROC} curve to reclassification and beyond},
journal = {Statistics in medicine},
year = {2008},
volume = {27},
pages = {157--172},
number = {2},
publisher = {Wiley Online Library}
}
@ARTICLE{PEN06,
author = {Pennec, Xavier and Fillard, Pierre and Ayache, Nicholas},
title = {A {R}iemannian Framework for Tensor Computing},
journal = {International Journal of Computer Vision},
year = {2006},
volume = {66},
pages = {41--66},
number = {1}
}
@ARTICLE{Penny2000EEG-based,
author = {Penny, W.D. and Roberts, S.J. and Curran, E.A. and Stokes, M.J.},
title = {{EEG}-based communication: a pattern recognition approach},
journal = {Rehabilitation Engineering, IEEE Transactions on},
year = {2000},
volume = {8},
pages = {214-215},
number = {2}
}
@ARTICLE{Pfurtscheller1992,
author = {Pfurtscheller},
title = {{Event-related synchronization ({ERS}): an electrophysiological correlate
of cortical areas at rest}},
journal = {Electroencephalography and Clinical Neurophysiology},
year = {1992},
volume = {83},
pages = {62-69},
number = {1}
}
@ARTICLE{Pfurtscheller1977Graph,
author = {Pfurtscheller, Gert},
title = {{Graphical display and statistical evaluation of event-related desynchronization
(ERD)}},
journal = {Electroencephalography and Clinical Neurophysiology},
year = {1977},
volume = {43},
pages = {757-760},
number = {5}
}
@ARTICLE{PFU10,
author = {Pfurtscheller, Gert and Allison, Brendan Z. and Brunner, Clemens
and Bauernfeind, Gunther and Solis-Escalante, Teodoro and Scherer,
Reinhold and Zander, Thorsten O. and Mueller-Putz, Gernot and Neuper,
Christa and Birbaumer, Niels},
title = {The hybrid {BCI}},
journal = {Frontiers in neuroscience},
year = {2010},
volume = {4}
}
@ARTICLE{Pfurtscheller1977Event,
author = {G Pfurtscheller and A Aranibar},
title = {{Event-related cortical desynchronization detected by power measurements
of scalp EEG}},
journal = {Electroencephalography and Clinical Neurophysiology},
year = {1977},
volume = {42},
pages = {817-826},
number = {6}
}
@ARTICLE{PFU93,
author = {Pfurtscheller, Gert and Flotzinger, Doris and Kalcher, Joachim},
title = {{Brain-Computer} Interface - a new communication device for handicapped
persons},
journal = {Journal of Microcomputer Applications},
year = {1993},
volume = {16},
pages = {293--299},
number = {3},
month = jul,
abstract = {A {Brain-Computer} Interface ({BCI}) is a system which can bypass
the normal motor output through the spine by using bioelectrical
signals recorded on the intact scalp during purely mental activity.
Such a {BCI} must be able to classify {EEG} patterns on-line and
can be used to control, e.g. the movement of a cursor on a monitor.
First results on a {BCI} developed in Graz are reported: 85\% correct
movements can be obtained after only a few days training.}
}
@ARTICLE{pfurtscheller1999ERDreview,
author = {Pfurtscheller, G. and Lopes da Silva, F. H.},
title = {{Event-related EEG/MEG synchronization and desynchronization: basic
principles.}},
journal = {Clinical Neurophysiology},
year = {1999},
volume = {110},
pages = {1842-1857},
number = {11}
}
@ARTICLE{pfurtscheller2001motorimagery,
author = {Pfurtscheller, G. and Neuper, C.},
title = {{Motor imagery and direct brain-computer communication}},
journal = {Proceedings of the IEEE},
year = {2001},
volume = {89},
pages = {1123-1134},
number = {7},
publisher = {IEEE}
}
@ARTICLE{Pfurtscheller1994Event,
author = {Gert Pfurtscheller and Christa Neuper},
title = {{Event-related synchronization of mu rhythm in the EEG over the cortical
hand area in man}},
journal = {Neuroscience Letters},
year = {1994},
volume = {174},
pages = {93-96},
number = {1}
}
@ARTICLE{Pfurtscheller2000,
author = {Pfurtscheller, G. and Neuper, C. and Guger, C. and Harkam, W. and
Ramoser, H. and Schlogl, A. and Obermaier, B. and Pregenzer, M.},
title = {{Current trends in {G}raz brain-computer interface ({BCI}) research}},
journal = {Rehabilitation Engineering, IEEE Transactions on},
year = {2000},
volume = {8},
pages = {216-219},
number = {2}
}
@ARTICLE{Pfurtscheller2010SelfPaced,
author = {Pfurtscheller, G. and Solis-Escalante, T. and Ortner, R. and Linortner,
P. and Muller-Putz, G.R.},
title = {{Self-Paced Operation of an SSVEP-Based Orthosis With and Without
an Imagery-Based Brain Switch: A Feasibility Study Towards a Hybrid
BCI}},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions
on},
year = {2010},
volume = {18},
pages = {409-414},
number = {4}
}
@ARTICLE{Pfurtscheller1997Onthe,
author = {G. Pfurtscheller and A Stanck and G Edlinger},
title = {{On the existence of different types of central beta rhythms below
30 Hz}},
journal = {Electroencephalography and Clinical Neurophysiology},
year = {1997},
volume = {102},
pages = {316-325},
number = {4}
}
@ARTICLE{Picton1992TheP300,
author = {Picton, Terence W.},
title = {{The P300 Wave of the Human Event-Related Potential}},
journal = {Journal of Clinical Neurophysiology},
year = {1992},
volume = {9},
pages = {456-479},
number = {4}
}
@ARTICLE{Pires2011,
author = {Gabriel Pires and Urbano Nunes and Miguel Castelo-Branco},
title = {{Statistical spatial filtering for a P300-based BCI: Tests in able-bodied,
and patients with cerebral palsy and amyotrophic lateral sclerosis}},
journal = {Journal of Neuroscience Methods},
year = {2011},
volume = {195},
pages = {270-281},
number = {2}
}
@ARTICLE{polich2007Updating,
author = {Polich, John},
title = {{Updating P300: an integrative theory of P3a and P3b.}},
journal = {Clinical Neurophysiology},
year = {2007},
volume = {118},
pages = {2128-2148},
number = {10}
}
@ARTICLE{Polich1991P300inEv,
author = {J Polich},
title = {P300 in the evaluation of aging and dementia},
journal = {Electroencephalogr Clin Neurophysiol Suppl},
year = {1991},
volume = {42},
pages = {304-23}
}
@ARTICLE{Rakotomamonjy2005,
author = {A. Rakotomamonjy and V. Guigue and G. Mallet and V. Alvarado},
title = {Ensemble of {SVM}s for improving brain-computer interface {P}300
speller performances},
journal = {15th International Conference on Artificial Neural Networks},
year = {2005},
pages = {45-50},
publisher = {Springer}
}
@ARTICLE{Ramoser2000,
author = {Ramoser, H. and Johannes M\"{u}ller-Gerking and Pfurtscheller, G.},
title = {{Optimal spatial filtering of single trial EEG during imagined hand
movement}},
journal = {IEEE Transactions on Neural Systems and Rehabilitation},
year = {2000},
volume = {8},
pages = {441-446}
}
@ARTICLE{Ren2008,
author = {Ren, R. and Guangyu Bin and Xiaorong Gao},
title = {Idle State Detection in SSVEP-Based Brain-Computer Interfaces},
journal = {Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The
2nd International Conference on},
year = {2008},
pages = {2012-2015},
month = {May}
}
@ARTICLE{REN10,
author = {Renard, Yann and Lotte, Fabien and Gibert, Guillaume and Congedo,
Marco and Maby, Emmanuel and Delannoy, Vincent and Bertrand, Olivier
and L\'{e}cuyer, Anatole},
title = {{OpenViBE}: An {Open-Source} Software Platform to Design, Test, and
Use {Brain--Computer} Interfaces in Real and Virtual Environments},
journal = {Presence: Teleoperators and Virtual Environments},
year = {2010},
volume = {19},
pages = {35--53},
number = {1},
abstract = {Abstract This paper describes the {OpenViBE} software platform which
enables researchers to design, test, and use brain?computer interfaces
({BCIs}). {BCIs} are communication systems that enable users to send
commands to computers solely by means of brain activity. {BCIs} are
gaining interest among the virtual reality ({VR}) community since
they have appeared as promising interaction devices for virtual environments
({VEs}). The key features of the platform are (1) high modularity,
(2) embedded tools for visualization and feedback based on {VR} and
{3D} displays, (3) {BCI} design made available to non-programmers
thanks to visual programming, and (4) various tools offered to the
different types of users. The platform features are illustrated in
this paper with two entertaining {VR} applications based on a {BCI}.
In the first one, users can move a virtual ball by imagining hand
movements, while in the second one, they can control a virtual spaceship
using real or imagined foot movements. Online experiments with these
applications together with the evaluation of the platform computational
performances showed its suitability for the design of {VR} applications
controlled with a {BCI}. {OpenViBE} is a free software distributed
under an open-source license.},
publisher = {MIT Press}
}
@ARTICLE{Ritter1969,
author = {Ritter, W and Vaughan, H G},
title = {Averaged evoked responses in vigilance and discrimination: a reassessment},
journal = {Science},
year = {1969},
volume = {164},
pages = {326-8},
number = {3877}
}
@ARTICLE{Rivet2009xDAWN,
author = {Rivet, B. and Souloumiac, A. and Attina, V. and Gibert, G.},
title = {{xDAWN} Algorithm to Enhance Evoked Potentials: Application to Brain-Computer
Interface},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2009},
volume = {56},
pages = {2035-2043},
number = {8}
}
@ARTICLE{Rivet2009xDAWNGSI,
author = {Rivet, B. and Souloumiac, A. and Attina, V. and Gibert, G.},
title = {{xDAWN} Algorithm to Enhance Evoked Potentials: Application to Brain-Computer
Interface},
journal = {IEEE Trans Biomed Eng},
year = {2009},
volume = {56},
pages = {2035-2043},
number = {8},
owner = {Quentin},
timestamp = {2015.03.09}
}
@ARTICLE{Millan2002,
author = {del R Millan, J. and Mourino, J. and Franze, M. and Cincotti, F.
and Varsta, M. and Heikkonen, J. and Babiloni, F.},
title = {{A local neural classifier for the recognition of EEG patterns associated
to mental tasks}},
journal = {Neural Networks, IEEE Transactions on},
year = {2002},
volume = {13},
pages = {678-686},
number = {3}
}
@INCOLLECTION{ROC11,
author = {Rocon, E. and Pons, J.},
title = {Introduction: {E}xoskeletons in Rehabilitation Robotics},
booktitle = {Springer Tracts in Advanced Robotics},
year = {2011},
volume = {69},
pages = {1--20},
abstract = {Rehabilitation Robotics has been defined as the combination of industrial
robotics and medical rehabilitation, thus encompassing many areas,
including mechanical and electrical engineering, biomedical engineering,
artificial intelligence and sensor and actuator technology. Medical
rehabilitation often refers to the process by which human function,
be it physical or cognitive, is restored at least partially to their
"normal" condition.}
}
@ARTICLE{Roland1980,
author = {P Roland and B Larsen and N Lassen and E Skinhoj},
title = {{Supplementary motor area and other cortical areas in organization
of voluntary movements in man}},
journal = {Neurophysiology},
year = {1980},
volume = {43},
pages = {118-136},
number = {1}
}
@INPROCEEDINGS{RYU10,
author = {Ryu, D. and Um, D. and Tanofsky, P. and Koh, D.H. and Ryu, Y.S. and
Kang, S.},
title = {T-less: {A} novel touchless human-machine interface based on infrared
proximity sensing},
booktitle = {Intelligent Robots and Systems (IROS)},
year = {2010},
pages = {5220--5225},
month = oct,
abstract = {In today's industry, intuitive gesture recognition, as manifested
in numerous consumer electronics devices, becomes a main issue of
{HMI} device research. Although finger-tip touch based user interface
has paved a main stream in mobile electronics, we envision touch-less
{HMI} as a promising technology in futuristic applications with higher
potential in areas where sanity or outdoor operation become of importance.
In this paper, we introduce a novel {HMI} device for non-contact
gesture input for intuitive {HMI} experiences. The enabling technology
of the proposed device is the {IPA} (infrared Proximity Array) sensor
by which realtime 3 dimensional depth information can be captured
and realized for machine control. For the usability study, two different
operating modes are adopted for hand motion inputs: one is a finger
tip control mode and the other is a palm control mode. Throughput
of the proposed device has been studied and compared to a traditional
mouse device for usability evaluation. During the human subject test,
the proposed device is found to be useful for {PC} mouse pointer
control. The experimental results are shared in the paper as well.}
}
@BOOK{Sornmo2005,
title = {Bioelectrical Signal Processing in Cardiac and Neurological Applications},
publisher = {Elsevier Academic Press},
year = {2005},
author = {Leif S\"{o}rnmo and Pablo Laguna},
isbn = {9780124375529}
}
@ARTICLE{SAD08,
author = {Sajda, P. and Muller, K. R. and Shenoy, K. V.},
title = {{Brain-Computer} Interfaces},
journal = {Signal Processing Magazine, IEEE},
year = {2008},
volume = {25},
pages = {16--17},
number = {1},
publisher = {IEEE}
}
@INPROCEEDINGS{samek2013robust,
author = {Samek, Wojciech and Blythe, Duncan and M{\"u}ller, Klaus-Robert and
Kawanabe, Motoaki},
title = {Robust spatial filtering with beta divergence},
booktitle = {Advances in Neural Information Processing Systems},
year = {2013},
pages = {1007--1015}
}
@INPROCEEDINGS{samek2014information,
author = {Samek, Wojciech and Muller, Klaus-Robert},
title = {Information geometry meets {BCI} spatial filtering using divergences},
booktitle = {Brain-Computer Interface (BCI), 2014 International Winter Workshop
on},
year = {2014},
pages = {1--4},
organization = {IEEE}
}
@ARTICLE{Satti2009,
author = {{Satti, A. and Coyle, D. and Prasad, G.}},
title = {{Continuous EEG classification for a self-paced BCI}},
journal = {{Neural Engineering, 2009. 4th International IEEE/EMBS Conference
on}},
year = {2009},
pages = {315-318}
}
@ARTICLE{schafer2005shrinkage,
author = {Sch{\"a}fer, Juliane and Strimmer, Korbinian},
title = {A shrinkage approach to large-scale covariance matrix estimation
and implications for functional genomics},
journal = {Statistical applications in genetics and molecular biology},
year = {2005},
volume = {4},
number = {1}
}
@ARTICLE{Scherer2007,
author = {R Scherer and G R M\"{u}ller-Putz and G Pfurtscheller},
title = {{Self-initiation of EEG-based brain-computer communication using
the heart rate response}},
journal = {Journal of Neural Engineering},
year = {2007},
volume = {4},
pages = {L23},
number = {4}
}
@ARTICLE{schettini2014self,
author = {Schettini, F and Aloise, F and Aric{\`o}, P and Salinari, S and Mattia,
D and Cincotti, F},
title = {Self-calibration algorithm in an asynchronous P300-based brain--computer
interface},
journal = {Journal of neural engineering},
year = {2014},
volume = {11},
pages = {035004},
number = {3},
publisher = {IOP Publishing}
}
@ARTICLE{schlogl2005motorimagery,
author = {Schl\"{o}gl, Alois and Lee, Felix and Bischof, Horst and Pfurtscheller,
Gert},
title = {{Characterization of four-class motor imagery EEG data for the BCI-competition
2005}},
journal = {Journal of Neural Engineering},
year = {2005},
volume = {2},
pages = {14--22},
number = {4}
}
@ARTICLE{Schott1993,
author = {Schoot, G.D.},
title = {{Penfield's homunculus: a note on cerebral cartography}},
journal = {Journal of Neurology, Neurosurgery, and Psychiatry},
year = {1993},
volume = {56},
pages = {329-333},
number = {4}
}
@ARTICLE{Sellers2006AP300Based,
author = {Sellers, Eric W. and Donchin, Emanuel},
title = {{A P300-based brain-computer interface: Initial tests by ALS patients}},
journal = {Clinical Neurophysiology},
year = {2006},
volume = {117},
pages = {538-548},
number = {3}
}
@ARTICLE{Sellers2006EffectOfMatrixSize,
author = {Eric W. Sellers and Dean J. Krusienski and Dennis J. McFarland and
Theresa M. Vaughan and Jonathan R. Wolpaw},
title = {{A P300 event-related potential brain-computer interface (BCI): The
effects of matrix size and inter stimulus interval on performance}},
journal = {Biological Psychology},
year = {2006},
volume = {73},
pages = {242-252},
number = {3}
}
@ARTICLE{SHE06,
author = {Shenoy, Pradeep and Krauledat, Matthias and Blankertz, Benjamin and
Rao, Rajesh P. N. and M\"{u}ller, Klaus-Robert},
title = {Towards adaptive classification for {BCI}},
journal = {Journal of Neural Engineering},
year = {2006},
volume = {3},
pages = {R13+},
number = {1},
month = mar
}
@ARTICLE{singer1993synchronization,
author = {Singer, W.},
title = {{Synchronization of Cortical Activity and its Putative Role in Information
Processing and Learning}},
journal = {Annual Review of Physiology},
year = {1993},
volume = {55},
pages = {349-374},
number = {1}
}
@INPROCEEDINGS{spuler2012one,
author = {Sp{\"u}ler, Martin and Rosenstiel, Wolfgang and Bogdan, Martin},
title = {One class {SVM} and Canonical Correlation Analysis increase performance
in a c-{VEP} based Brain-Computer Interface ({BC}I)},
booktitle = {Proceedings of 20th European Symposium on Artificial Neural Networks
(ESANN 2012), Bruges, Belgium},
year = {2012},
volume = {4},
pages = {103--108}
}
@ARTICLE{Stapleton1987Endogenous,
author = {J.M. Stapleton and E. Halgren},
title = {Endogenous potentials evoked in simple cognitive tasks: depth components
and task correlates},
journal = {Electroencephalography and Clinical Neurophysiology},
year = {1987},
volume = {67},
pages = {44-52},
number = {1}
}
@ARTICLE{Sterman1996,
author = {Sterman, M. Barry and Kaiser, David A. and Veigel, Bettina},
title = {{Spectral analysis of event-related EEG responses during short-term
memory performance}},
journal = {Brain Topography},
year = {1996},
volume = {9},
pages = {21-30},
issue = {1}
}
@ARTICLE{Sun2010,
author = {Hongyu Sun and Yang Xiang and Yaoru Sun and Huaping Zhu and Jinhua
Zeng},
title = {{On-line EEG classification for brain-computer interface based on
CSP and SVM}},
journal = {Image and Signal Processing (CISP), 2010 3rd International Congress
on},
year = {2010},
volume = {9},
pages = {4105-4108}
}
@ARTICLE{Sutton1965EPCorr,
author = {Sutton, S. and Braren, M. and Zubin, J. and John, E. R.},
title = {{Evoked-potential Correlates of Stimulus Uncertainty}},
journal = {Science},
year = {1965},
volume = {150},
pages = {1187-1188}
}
@ARTICLE{Sutton1967Inform,
author = {Sutton, Samuel and Tueting, Patricia and Zubin, Joseph and John,
E. R.},
title = {{Information Delivery and the Sensory Evoked Potential}},
journal = {Science},
year = {1967},
volume = {155},
pages = {1436-1439},
number = {3768}
}
@ARTICLE{Szuromi2010,
author = {B Szuromi and P Czobor and S Komlosi and I Bitter},
title = {{P300 deficits in adults with attention deficit hyperactivity disorder:
a meta-analysis}},
journal = {Psychol Med.},
year = {2010},
volume = {41},
pages = {1529-1538},
number = {7}
}
@ARTICLE{TAN12,
author = {Tangermann, Michael and M{\"u}ller, Klaus-Robert and Aertsen, Ad
and Birbaumer, Niels and Braun, Christoph and Brunner, Clemens and
Leeb, Robert and Mehring, Carsten and Miller, Kai J and Mueller-Putz,
Gernot and Nolte, Guido and Pfurtscheller, Gert and Preissl, Hubert
and Schalk, Gerwin and Schl{\"o}gl, Alois and Vidaurre, Carmen and
Waldert, Stephan and Blankertz, Benjamin},
title = {{Review of the BCI Competition IV}},
journal = {Frontiers in Neuroscience},
year = {2012},
volume = {6},
number = {55},
abstract = {The BCI Competition IV stands in the tradition of prior BCI Competitions
that aim to provide high quality neuroscientific data for open access
to the scientific community. As experienced already in prior competitions
not only scientists from the narrow field of BCI compete, but scholars
with a broad variety of backgrounds and nationalities. They include
high specialists as well as students. The goals of all BCI Competitions
have always been to challenge with respect to novel paradigms and
complex data. We report on the following challenges: (1) asynchronous
data, (2) synthetic, (3) multi-class continuous data, (4) session-to-session
transfer, (5) directionally modulated MEG, (6) finger movements recorded
by ECoG. As after past competitions, our hope is that winning entries
may enhance the analysis methods of future BCIs.}
}
@ARTICLE{Teli2009,
author = {Mohammad Nayeem Teli and Charles Anderson},
title = {{Nonlinear dimensionality reduction of electroencephalogram (EEG)
for Brain Computer interfaces}},
journal = {Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual
International Conference of the IEEE},
year = {2009},
pages = {2486-2489}
}
@ARTICLE{tiganj2012,
author = {Tiganj, Zoran and Mboup, Mamadou and Chevallier, Sylvain and Kalunga,
Emmanuel},
title = {{Online frequency band estimation and change-point detection}},
journal = {{Systems and Computer Science (ICSCS), 2012 1st International Conference
on}},
year = {2012},
pages = {1-6}
}
@ARTICLE{Ting2008,
author = {Wu Ting and Yan Guo-zheng and Yang Bang-hua and Sun Hong},
title = {{EEG feature extraction based on wavelet packet decomposition for
brain computer interface}},
journal = {Measurement},
year = {2008},
volume = {41},
pages = {618-625},
number = {6}
}
@INPROCEEDINGS{TOM07,
author = {Tomioka, Ryota and Aihara, Kazuyuki and M{\"u}ller, Klaus-Robert},
title = {Logistic regression for single trial {EEG} classification},
booktitle = {Advances in neural information processing systems (NIPS)},
year = {2007},
volume = {19},
pages = {1377--1384}
}
@INPROCEEDINGS{TOM07GSI,
author = {Tomioka, Ryota and Aihara, Kazuyuki and M{\"u}ller, Klaus-Robert},
title = {Logistic regression for single trial {EEG} classification},
booktitle = {NIPS},
year = {2007},
volume = {19},
pages = {1377--1384},
owner = {Quentin},
timestamp = {2015.03.09}
}
@ARTICLE{Toro1994Event,
author = {{Toro, C. and Deuschl, G and Thatcher, R and Sato, S. and Kufta,
C and Hallett, M.}},
title = {Event-related desynchronization and movement-related cortical potentials
on the {ECoG} and {EEG}},
journal = {{Electroencephalography and Clinical Neurophysiology/Evoked Potentials
Section}},
year = {1994},
volume = {93},
pages = {380-389},
number = {5}
}
@ARTICLE{Trad2011,
author = {Trad, D. and Al-ani, T. and Monacelli, E. and Jemni, M.},
title = {Nonlinear and nonstationary framework for feature extraction and
classification of motor imagery},
journal = {Rehabilitation Robotics (ICORR), 2011 IEEE International Conference
on},
year = {2011},
pages = {1-6}
}
@ARTICLE{TU12,
author = {Tu, Wenting and Sun, Shiliang},
title = {A subject transfer framework for {EEG} classification},
journal = {Neurocomputing},
year = {2012},
volume = {82},
pages = {109--116}
}
@INCOLLECTION{verschore2012dynamic,
author = {Verschore, Hannes and Kindermans, Pieter-Jan and Verstraeten, David
and Schrauwen, Benjamin},
title = {{Dynamic stopping improves the speed and accuracy of a P300 speller}},
booktitle = {Artificial Neural Networks and Machine Learning--ICANN 2012},
publisher = {Springer},
year = {2012},
pages = {661--668}
}
@ARTICLE{VID73,
author = {Vidal, J. J.},
title = {Toward direct brain-computer communication.},
journal = {Annual review of biophysics and bioengineering},
year = {1973},
volume = {2},
pages = {157--180},
number = {1}
}
@ARTICLE{VID10,
author = {Vidaurre, Carmen and Blankertz, Benjamin},
title = {{Towards a cure for {BCI} illiteracy.}},
journal = {Brain topography},
year = {2010},
volume = {23},
pages = {194--198},
number = {2},
abstract = {{Brain-Computer} Interfaces ({BCIs}) allow a user to control a computer
application by brain activity as acquired, e.g., by {EEG}. One of
the biggest challenges in {BCI} research is to understand and solve
the problem of \"{BCI} Illiteracy\", which is that {BCI} control
does not work for a non-negligible portion of users (estimated 15
to 30\%). Here, we investigate the illiteracy problem in {BCI} systems
which are based on the modulation of sensorimotor rhythms. In this
paper, a sophisticated adaptation scheme is presented which guides
the user from an initial subject-independent classifier that operates
on simple features to a subject-optimized state-of-the-art classifier
within one session while the user interacts the whole time with the
same feedback application. While initial runs use supervised adaptation
methods for robust co-adaptive learning of user and machine, final
runs use unsupervised adaptation and therefore provide an unbiased
measure of {BCI} performance. Using this approach, which does not
involve any offline calibration measurement, good performance was
obtained by good {BCI} participants (also one novice) after 3-6 min
of adaptation. More importantly, the use of machine learning techniques
allowed users who were unable to achieve successful feedback before
to gain significant control over the {BCI} system. In particular,
one participant had no peak of the sensory motor idle rhythm in the
beginning of the experiment, but could develop such peak during the
course of the session (and use voluntary modulation of its amplitude
to control the feedback application).},
booktitle = {{Brain Topography}}
}
@ARTICLE{Wang2011HHT,
author = {Lei Wang and Guizhi Xu and Jiang Wang and Shuo Yang and Weili Yan},
title = {{Motor Imagery BCI Research Based on Hilbert-Huang Transform and
Genetic Algorithm}},
journal = {Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International
Conference on},
year = {2011},
pages = {1-4}
}
@INPROCEEDINGS{Wang2006,
author = {Wang, Suogang and James, Christopher J.},
title = {Enhancing Evoked Responses for {BCI} Through Advanced {ICA} Techniques},
booktitle = {Advances in Medical, Signal and Information Processing (MEDSIP)},
year = {2006},
pages = {1-4}
}
@INPROCEEDINGS{Wang2006GSI,
author = {Wang, Suogang and James, Christopher J.},
title = {Enhancing Evoked Responses for {BCI} Through Advanced {ICA} Techniques},
booktitle = {MEDSIP},
year = {2006},
pages = {1-4},
owner = {Quentin},
timestamp = {2015.03.09}
}
@ARTICLE{Wang2013,
author = {Wang, Yijun and Jung, Tzyy-Ping},
title = {Improving Brain-computer Interfaces Using Independent Component Analysis},
journal = {Towards Practical Brain-Computer Interfaces},
year = {2013},
pages = {67-83}
}
@ARTICLE{Wang2004,
author = {Yijun Wang and Zhiguang Zhang and Xiaorong Gao and Shangkai Gao},
title = {{Lead selection for SSVEP-based brain-computer interface}},
journal = {Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th
Annual International Conference of the IEEE},
year = {2004},
volume = {2},
pages = {4507-4510}
}
@ARTICLE{Wilson2006ECoG,
author = {Wilson, J.A. and Felton, E.A. and Garell, P.C. and Schalk, G. and
Williams, J.C.},
title = {{ECoG factors underlying multimodal control of a brain-computer interface}},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions
on},
year = {2006},
volume = {14},
pages = {246-250},
number = {2}
}
@ARTICLE{WOL02,
author = {Wolpaw, J. and Birbaumer, N. and McFarland, D. J. and Pfurtscheller,
G. and Vaughan, T. M.},
title = {{Brain--computer interfaces for communication and control}},
journal = {Clinical Neurophysiology},
year = {2002},
volume = {113},
pages = {767--791},
number = {6},
month = jun
}
@ARTICLE{wolpaw2002bcireview,
author = {Wolpaw, Jonathan R. and Birbaumer, Niels and McFarland, Dennis J.
and Pfurtscheller, Gert and Vaughan, Theresa M.},
title = {{Brain-computer interfaces for communication and control}},
journal = {Clinical Neurophysiology},
year = {2002},
volume = {113},
pages = {767-791},
number = {6}
}
@ARTICLE{Wolpaw1991,
author = {Jonathan R. Wolpaw and Dennis J. McFarland and Gregory W. Neat and
Catherine A. Forneris},
title = {An {EEG}-based brain-computer interface for cursor control},
journal = {Electroencephalography and Clinical Neurophysiology},
year = {1991},
volume = {78},
pages = {252-259},
number = {3}
}
@ARTICLE{Wolpaw2000,
author = {Jonathan R. Wolpaw. and Birbaumer, N. and Heetderks, W.J. and Dennis
J. McFarland and Peckham, P.H. and Schalk, G. and Donchin, E. and
Quatrano, L.A. and Robinson, C.J. and Vaughan, T.M.},
title = {{Brain-computer interface technology: a review of the first international
meeting}},
journal = {Rehabilitation Engineering, IEEE Transactions on},
year = {2000},
volume = {8},
pages = {164-173},
number = {2}
}
@INPROCEEDINGS{xie2013nonlinear,
author = {Xie, Yuchen and Ho, Jeffrey and Vemuri, Baba},
title = {On A Nonlinear Generalization of Sparse Coding and Dictionary Learning},
booktitle = {Proceedings of the 30th International Conference on Machine Learning},
year = {2013},
pages = {1480},
organization = {NIH Public Access}
}
@ARTICLE{Yan2008,
author = {Tang Yan and Tang Jingtian and Gong Andong and Wang Wei},
title = {{Classifying EEG Signals Based HMM-AR}},
journal = {Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The
2nd International Conference on},
year = {2008},
pages = {2111-2114}
}
@INPROCEEDINGS{YAN12a,
author = {Yang, Y. and Chevallier, S. and Wiart, J. and Bloch, I.},
title = {{Automatic selection of the number of spatial filters for motor-imagery
BCI}},
booktitle = {{European Symposium on Artificial Neural Networks (ESANN)}},
year = {2012},
editor = {Verleysen, M.},
pages = {109--114},
abstract = {Common Spatial Pattern (CSP) is widely used for constructing spatial
filters to extract features for motor-imagery-based BCI. One main
parameter in CSP-based classification is the number of spatial filters
used. An automatic method relying on Rayleigh quotient is presented
to estimate its optimal value for each subject. Based on an existing
dataset, we validate the contribution of the proposed method through
a study of the effect of this parameter on the classification performance.
The evaluation on testing data shows that the estimated subject-specific
optimal values yield better performances than the recommanded value
in the literature.}
}
@INPROCEEDINGS{yger2013review,
author = {Yger, Florian},
title = {{A review of kernels on covariance matrices for BCI applications}},
booktitle = {Machine Learning for Signal Processing (MLSP), 2013 IEEE International
Workshop on},
year = {2013},
pages = {1--6},
organization = {IEEE}
}
@ARTICLE{YIN13,
author = {Yin, Erwei and Zhou, Zongtan and Jiang, Jun and Chen, Fanglin and
Liu, Yadong and Hu, Dewen},
title = {A novel hybrid {BCI} speller based on the incorporation of {SSVEP}
into the P300 paradigm},
journal = {Journal of Neural Engineering},
year = {2013},
volume = {10},
number = {2},
abstract = {Objective. Although extensive studies have shown improvement in spelling
accuracy, the conventional P300 speller often exhibits errors, which
occur in almost the same row or column relative to the target. To
address this issue, we propose a novel hybrid brain-computer interface
({BCI}) approach by incorporating the steady-state visual evoked
potential ({SSVEP}) into the conventional P300 paradigm. Approach.
We designed a periodic stimuli mechanism and superimposed it onto
the P300 stimuli to increase the difference between the symbols in
the same row or column. Furthermore, we integrated the random flashings
and periodic flickers to simultaneously evoke the P300 and {SSVEP},
respectively. Finally, we developed a hybrid detection mechanism
based on the P300 and {SSVEP} in which the target symbols are detected
by the fusion of three-dimensional, time-frequency features. Main
results. The results obtained from 12 healthy subjects show that
an online classification accuracy of 93.85\% and information transfer
rate of 56.44 bit/min were achieved using the proposed {BCI} speller
in only a single trial. Specifically, 5 of the 12 subjects exhibited
an information transfer rate of 63.56 bit/min with an accuracy of
100\%. Significance . The pilot studies suggested that the proposed
{BCI} speller could achieve a better and more stable system performance
compared with the conventional P300 speller, and it is promising
for achieving quick spelling in stimulus-driven {BCI} applications.}
}
@ARTICLE{ZAN11,
author = {Zander, Thorsten O. and Kothe, Christian},
title = {Towards passive brain--computer interfaces: applying brain--computer
interface technology to human--machine systems in general},
journal = {Journal of Neural Engineering},
year = {2011},
volume = {8},
pages = {025005+},
number = {2},
publisher = {IOP Publishing}
}
@ARTICLE{Zhang2008,
author = {Haihong Zhang and Cuntai Guan and Chuanchu Wang},
title = {{Asynchronous P300-Based Brain--Computer Interfaces: A Computational
Approach With Statistical Models}},
journal = {Biomedical Engineering, IEEE Transactions on},
year = {2008},
volume = {55},
pages = {1754-1763},
number = {6}
}
@ARTICLE{Zhang2007P300,
author = {Jia-Cai Zhang and Ya-Qin Xu and Li Yao},
title = {{P300 Detection Using Boosting Neural Networks with Application to
BCI}},
journal = {Complex Medical Engineering, 2007. CME 2007. IEEE/ICME International
Conference on},
year = {2007},
pages = {1526-1530}
}
@ARTICLE{Zhang2010,
author = {Liwei Zhang and Guozhong Liu and Ying Wu},
title = {{Wavelet and Common Spatial Pattern for EEG signal feature extraction
and classification}},
journal = {Computer, Mechatronics, Control and Electronic Engineering (CMCE),
2010 International Conference on},
year = {2010},
volume = {5},
pages = {243-246}
}
@ARTICLE{Zhu2010aSurvey,
author = {Zhu, Danhua and Bieger, Jordi and Molina, Gary Garcia and Aarts,
Ronald M.},
title = {{A survey of stimulation methods used in SSVEP-based BCIs}},
journal = {Intell. Neuroscience},
year = {2010},
volume = {2010},
pages = {1-12},
issn = {1687-5265}
}
@INCOLLECTION{ZHU11,
author = {Zhu, Danhua and Garcia-Molina, Gary and Mihajlovi\'{c}, Vojkan and
Aarts, RonaldM},
title = {Online {BCI} Implementation of {High-Frequency} Phase Modulated Visual
Stimuli},
booktitle = {Universal Access in Human-Computer Interaction. Users Diversity},
publisher = {Springer Berlin Heidelberg},
year = {2011},
editor = {Stephanidis, Constantine},
volume = {6766},
series = {Lecture Notes in Computer Science},
pages = {645--654}
}
@ARTICLE{Zou2010,
author = {Ling Zou and Xinguang Wang and Guodong Shi and Zhenghua Ma},
title = {{EEG feature extraction and pattern classification based on motor
imagery in brain-computer interface}},
journal = {Cognitive Informatics (ICCI), 2010 9th IEEE International Conference
on},
year = {2010},
pages = {536-541}
}
@ARTICLE{Hoffmann2008,
title = {{An efficient P300-based brain-computer interface for disabled subjects}},
journal = {Journal of Neuroscience Methods},
year = {2008},
volume = {167},
pages = {115-125},
number = {1}
}
@inproceedings{barachant_p300-speller:_2015,
title = {P300-speller: {Géométrie} {Riemannienne} pour la détection multi-sujets de potentiels d'erreur},
shorttitle = {P300-speller},
url = {https://hal.archives-ouvertes.fr/hal-01255363/},
urldate = {2016-06-01},
booktitle = {{GRETSI} 2015},
author = {Barachant, Alexandre and Cycon, Rafa{\textbackslash}l and Gouy-Pailler, Cedric},
year = {2015},
file = {[PDF] from archives-ouvertes.fr:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QV2794RS/Barachant et al. - 2015 - P300-speller Géométrie Riemannienne pour la détec.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/XG7Z5WPQ/hal-01255363.html:text/html}
}
@article{heisz_automatic_2006,
title = {Automatic face identity encoding at the {N}170},
volume = {46},
url = {http://www.sciencedirect.com/science/article/pii/S0042698906004573},
number = {28},
urldate = {2016-02-01},
journal = {Vision Research},
author = {Heisz, Jennifer J. and Watter, Scott and Shedden, Judith M.},
year = {2006},
pages = {4604--4614},
file = {[HTML] à partir de sciencedirect.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/XI44RV33/S0042698906004573.html:text/html}
}
@article{eimer_face-specific_2000,
title = {The face-specific {N}170 component reflects late stages in the structural encoding of faces},
volume = {11},
url = {http://journals.lww.com/neuroreport/Abstract/2000/07140/The_face_specific_N170_component_reflects_late.50.aspx},
number = {10},
urldate = {2016-02-03},
journal = {Neuroreport},
author = {Eimer, Martin},
year = {2000},
pages = {2319--2324},
file = {[PDF] from uj.edu.pl:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/8VZRU3NS/Eimer - 2000 - The face-specific N170 component reflects late sta.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/PHSB36UZ/The_face_specific_N170_component_reflects_late.50.html:text/html}
}
@article{blankertz_bci_2004,
title = {The {BCI} competition 2003: progress and perspectives in detection and discrimination of {EEG} single trials},
volume = {51},
abstract = {Interest in developing a new method of man-to-machine communication-a brain-computer interface (BCI)-has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, the surface of the cortex, or from inside the brain to enable users to control a variety of applications including simple word-processing software and orthotics. BCI technology could therefore provide a new communication and control option for individuals who cannot otherwise express their wishes to the outside world. Signal processing and classification methods are essential tools in the development of improved BCI technology. We organized the BCI Competition 2003 to evaluate the current state of the art of these tools. Four laboratories well versed in EEG-based BCI research provided six data sets in a documented format. We made these data sets (i.e., labeled training sets and unlabeled test sets) and their descriptions available on the Internet. The goal in the competition was to maximize the performance measure for the test labels. Researchers worldwide tested their algorithms and competed for the best classification results. This paper describes the six data sets and the results and function of the most successful algorithms.},
number = {6},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Blankertz, Benjamin and Müller, Klaus-Robert R. and Curio, Gabriel and Vaughan, Theresa M. and Schalk, Gerwin and Wolpaw, Jonathan R. and Schlögl, Alois and Neuper, Christa and Pfurtscheller, Gert and Hinterberger, Thilo and Schröder, Michael and Birbaumer, Niels},
year = {2004},
pages = {1044--1051}
}
@article{paetau_magnetoencephalography_2002,
title = {Magnetoencephalography in pediatric neuroimaging},
volume = {5},
url = {http://onlinelibrary.wiley.com/doi/10.1111/1467-7687.00375/full},
number = {3},
urldate = {2016-04-19},
journal = {Developmental Science},
author = {Paetau, Ritva},
year = {2002},
pages = {361--370},
file = {[PDF] from duke.edu:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/DJXW9CN6/Paetau - 2002 - Magnetoencephalography in pediatric neuroimaging.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/UEVB6RCQ/full.html:text/html}
}
@book{nielsen_matrix_2012,
title = {Matrix {Information} {Geometry}},
publisher = {Springer Publishing Company, Incorporated},
author = {Nielsen, Frank and Bhatia, Rajendra},
year = {2012}
}
@article{power_automatic_2012,
title = {Automatic single-trial discrimination of mental arithmetic, mental singing and the no-control state from prefrontal activity: toward a three-state {NIRS}-{BCI}},
volume = {5},
issn = {1756-0500},
shorttitle = {Automatic single-trial discrimination of mental arithmetic, mental singing and the no-control state from prefrontal activity},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3359174/},
doi = {10.1186/1756-0500-5-141},
abstract = {Background
Near-infrared spectroscopy (NIRS) is an optical imaging technology that has recently been investigated for use in a safe, non-invasive brain-computer interface (BCI) for individuals with severe motor impairments. To date, most NIRS-BCI studies have attempted to discriminate two mental states (e.g., a mental task and rest), which could potentially lead to a two-choice BCI system. In this study, we attempted to automatically differentiate three mental states - specifically, intentional activity due to 1) a mental arithmetic (MA) task and 2) a mental singing (MS) task, and 3) an unconstrained, "no-control (NC)" state - to investigate the feasibility of a three-choice system-paced NIRS-BCI.
Results
Deploying a dual-wavelength frequency domain near-infrared spectrometer, we interrogated nine sites around the frontopolar locations while 7 able-bodied adults performed mental arithmetic and mental singing to answer multiple-choice questions within a system-paced paradigm. With a linear classifier trained on a ten-dimensional feature set, an overall classification accuracy of 56.2\% was achieved for the MA vs. MS vs. NC classification problem and all individual participant accuracies significantly exceeded chance (i.e., 33\%). However, as anticipated based on results of previous work, the three-class discrimination was unsuccessful for three participants due to the ineffectiveness of the mental singing task. Excluding these three participants increases the accuracy rate to 62.5\%. Even without training, three of the remaining four participants achieved accuracies approaching 70\%, the value often cited as being necessary for effective BCI communication.
Conclusions
These results are encouraging and demonstrate the potential of a three-state system-paced NIRS-BCI with two intentional control states corresponding to mental arithmetic and mental singing.},
urldate = {2016-04-19},
journal = {BMC Research Notes},
author = {Power, Sarah D and Kushki, Azadeh and Chau, Tom},
month = mar,
year = {2012},
pmid = {22414111},
pmcid = {PMC3359174},
pages = {141},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/6E9JHIWW/Power et al. - 2012 - Automatic single-trial discrimination of mental ar.pdf:application/pdf}
}
@article{mcfarland_bci_2006,
title = {{BCI} meeting 2005-workshop on {BCI} signal processing: feature extraction and translation},
volume = {14},
number = {2},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {McFarland, D.J. and Anderson, C.W. and Muller, K.R. and Schlogl, A. and Krusienski, D.J.},
year = {2006},
pages = {135--138}
}
@article{grubler_psychosocial_2014,
title = {Psychosocial and {Ethical} {Aspects} in {Non}-{Invasive} {EEG}-{Based} {BCI} {Research}—{A} {Survey} {Among} {BCI} {Users} and {BCI} {Professionals}},
volume = {7},
issn = {1874-5490, 1874-5504},
url = {http://link.springer.com/10.1007/s12152-013-9179-7},
doi = {10.1007/s12152-013-9179-7},
language = {en},
number = {1},
urldate = {2016-04-21},
journal = {Neuroethics},
author = {Grübler, Gerd and Al-Khodairy, Abdul and Leeb, Robert and Pisotta, Iolanda and Riccio, Angela and Rohm, Martin and Hildt, Elisabeth},
month = apr,
year = {2014},
pages = {29--41}
}
@article{pennec_riemannian_2006,
title = {A {Riemannian} {Framework} for {Tensor} {Computing}},
volume = {66},
number = {1},
journal = {International Journal of Computer Vision},
author = {Pennec, Xavier and Fillard, Pierre and Ayache, Nicholas},
year = {2006},
pages = {41--66}
}
@article{leuthardt_brain-computer_2004,
title = {A brain-computer interface using electrocorticographic signals in humans},
volume = {1},
issn = {1741-2560},
doi = {10.1088/1741-2560/1/2/001},
abstract = {Brain-computer interfaces (BCIs) enable users to control devices with electroencephalographic (EEG) activity from the scalp or with single-neuron activity from within the brain. Both methods have disadvantages: EEG has limited resolution and requires extensive training, while single-neuron recording entails significant clinical risks and has limited stability. We demonstrate here for the first time that electrocorticographic (ECoG) activity recorded from the surface of the brain can enable users to control a one-dimensional computer cursor rapidly and accurately. We first identified ECoG signals that were associated with different types of motor and speech imagery. Over brief training periods of 3-24 min, four patients then used these signals to master closed-loop control and to achieve success rates of 74-100\% in a one-dimensional binary task. In additional open-loop experiments, we found that ECoG signals at frequencies up to 180 Hz encoded substantial information about the direction of two-dimensional joystick movements. Our results suggest that an ECoG-based BCI could provide for people with severe motor disabilities a non-muscular communication and control option that is more powerful than EEG-based BCIs and is potentially more stable and less traumatic than BCIs that use electrodes penetrating the brain.},
language = {eng},
number = {2},
journal = {Journal of Neural Engineering},
author = {Leuthardt, Eric C. and Schalk, Gerwin and Wolpaw, Jonathan R. and Ojemann, Jeffrey G. and Moran, Daniel W.},
month = jun,
year = {2004},
pmid = {15876624},
keywords = {Adult, Brain, Communication Aids for Disabled, Computer Peripherals, Diagnosis, Computer-Assisted, Electrodes, Implanted, Electroencephalography, Evoked Potentials, Female, Humans, Imagination, Male, Movement Disorders, User-Computer Interface},
pages = {63--71}
}
@article{obermaier_hidden_2001,
title = {Hidden {Markov} models for online classification of single trial {EEG} data},
volume = {22},
number = {12},
journal = {Pattern Recognition Letters},
author = {Obermaier, B. and Guger, C. and Neuper, C. and Pfurtscheller, G.},
year = {2001},
pages = {1299--1309}
}
@article{mellinger_meg-based_2007,
title = {An {MEG}-based {Brain}-{Computer} {Interface} ({BCI})},
volume = {36},
issn = {1053-8119},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2017111/},
doi = {10.1016/j.neuroimage.2007.03.019},
abstract = {Brain-Computer Interfaces (BCIs) allow for communicating intentions by mere brain activity, not involving muscles. Thus, BCIs may offer patients who have lost all voluntary muscle control the only possible way to communicate. Many recent studies have demonstrated that BCIs based on electroencephalography (EEG) can allow healthy and severely paralyzed individuals to communicate. While this approach is safe and inexpensive, communication is slow. Magnetoencephalography (MEG) provides signals with higher spatiotemporal resolution than EEG, and could thus be used to explore whether these improved signal properties translate into increased BCI communication speed. In this study, we investigated the utility of an MEG-based BCI that uses voluntary amplitude modulation of sensorimotor μ and β rhythms. To increase the signal-to-noise ratio, we present a simple spatial filtering method that takes the geometric properties of signal propagation in MEG into account, and we present methods that can process artifacts specifically encountered in an MEG-based BCI. Exemplarily, six participants were successfully trained to communicate binary decisions by imagery of limb movements using a feedback paradigm. Participants achieved significant μ-rhythm self control within 32 minutes of feedback training. For a subgroup of three participants, we localized the origin of the amplitude modulated signal to the motor cortex. Our results suggest that an MEG-based BCI is feasible and efficient in terms of user training.},
number = {3},
urldate = {2016-04-19},
journal = {NeuroImage},
author = {Mellinger, Jürgen and Schalk, Gerwin and Braun, Christoph and Preissl, Hubert and Rosenstiel, Wolfgang and Birbaumer, Niels and Kübler, Andrea},
month = jul,
year = {2007},
pmid = {17475511},
pmcid = {PMC2017111},
pages = {581--593},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/PMFWU5N9/Mellinger et al. - 2007 - An MEG-based Brain-Computer Interface (BCI).pdf:application/pdf}
}
@article{hoffmann_boosting_2005,
title = {A {Boosting} {Approach} to {P}300 {Detection} with {Application} to {Brain}-{Computer} {Interfaces}},
journal = {Neural Engineering, 2005. Conference Proceedings. 2nd International IEEE EMBS Conference on},
author = {Hoffmann, U. and Garcia, G. and Vesin, J.-M. and Diserens, K. and Ebrahimi, T.},
year = {2005},
pages = {97--100}
}
@article{singer_synchronization_1993,
title = {Synchronization of {Cortical} {Activity} and its {Putative} {Role} in {Information} {Processing} and {Learning}},
volume = {55},
number = {1},
journal = {Annual Review of Physiology},
author = {Singer, W.},
year = {1993},
pages = {349--374}
}
@article{ang_filter_2012,
title = {Filter {Bank} {Common} {Spatial} {Pattern} {Algorithm} on {BCI} {Competition} {IV} {Datasets} 2a and 2b.},
volume = {6},
journal = {Frontiers in neuroscience},
author = {Ang, Kai Keng K. and Chin, Zheng Yang Y. and Wang, Chuanchu and Guan, Cuntai and Zhang, Haihong},
year = {2012}
}
@article{purves_excitatory_2001,
title = {Excitatory and {Inhibitory} {Postsynaptic} {Potentials}},
url = {http://www.ncbi.nlm.nih.gov/books/NBK11117/},
abstract = {Postsynaptic conductance changes and the potential changes that accompany them alter the probability that an action potential will be produced in the postsynaptic cell. At the neuromuscular junction, synaptic action increases the probability that an action potential will occur in the postsynaptic muscle cell; indeed, the large amplitude of the EPP ensures that an action potential always is triggered. At many other synapses, PSPs actually decrease the probability that the postsynaptic cell will generate an action potential. PSPs are called excitatory (or EPSPs) if they increase the likelihood of a postsynaptic action potential occurring, and inhibitory (or IPSPs) if they decrease this likelihood. Given that most neurons receive inputs from both excitatory and inhibitory synapses, it is important to understand more precisely the mechanisms that determine whether a particular synapse excites or inhibits its postsynaptic partner.},
language = {en},
urldate = {2016-04-14},
author = {Purves, Dale and Augustine, George J. and Fitzpatrick, David and Katz, Lawrence C. and LaMantia, Anthony-Samuel and McNamara, James O. and Williams, S. Mark},
year = {2001},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/KIZVFFTP/NBK11117.html:text/html}
}
@article{lotte_pattern_2008,
title = {Pattern rejection strategies for the design of self-paced {EEG}-based {Brain}-{Computer} {Interfaces}.},
journal = {ICPR},
author = {Lotte, Fabien and Mouchère, Harold and Lécuyer, Anatole},
year = {2008},
pages = {1--5}
}
@article{gucluturk_online_2010,
title = {An online single trial analysis of the {P}300 event related potential for the disabled},
journal = {Electrical and Electronics Engineers in Israel (IEEEI), 2010 IEEE 26th Convention of},
author = {Güçlütürk, Y. and Güçlü, U. and Samraj, A.},
year = {2010},
pages = {338--341}
}
@article{lemm_bci_2004,
title = {{BCI} competition 2003-data set {III}: probabilistic modeling of sensorimotor mu; rhythms for classification of imaginary hand movements},
volume = {51},
number = {6},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Lemm, S. and Schafer, C. and Curio, G.},
year = {2004},
pages = {1077--1080}
}
@inproceedings{seguy_principal_2015,
title = {Principal {Geodesic} {Analysis} for {Probability} {Measures} under the {Optimal} {Transport} {Metric}},
url = {http://papers.nips.cc/paper/5680-projective-dictionary-pair-learning-for-pattern-classification},
urldate = {2016-02-18},
booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
author = {Seguy, Vivien and Cuturi, Marco},
year = {2015},
pages = {3294--3302},
file = {[HTML] à partir de nips.cc:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/2E7AEDWZ/5680-projective-dictionary-pair-learning-for-pattern-classification.html:text/html;[HTML] à partir de nips.cc:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/S8FRRI3U/5680-projective-dictionary-pair-learning-for-pattern-classification.html:text/html}
}
@inproceedings{goh_clustering_2008,
title = {Clustering and dimensionality reduction on {Riemannian} manifolds},
booktitle = {Computer {Vision} and {Pattern} {Recognition}, 2008. {CVPR} 2008. {IEEE} {Conference} on},
publisher = {IEEE},
author = {Goh, Alvina and Vidal, René},
year = {2008},
pages = {1--7}
}
@article{karcher_riemannian_1977,
title = {Riemannian center of mass and mollifier smoothing},
volume = {30},
number = {5},
journal = {Comm. Pure Appl. Math.},
author = {Karcher, H.},
month = sep,
year = {1977},
pages = {509--541}
}
@article{guger_rapid_2001,
title = {Rapid prototyping of an {EEG}-based brain-computer interface ({BCI})},
volume = {9},
number = {1},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {Guger, C. and Schlogl, A. and Neuper, C. and Walterspacher, D. and Strein, T. and Pfurtscheller, G.},
year = {2001},
pages = {49--58}
}
@article{deng_improved_2012,
title = {Improved {Surface} {Laplacian} {Estimates} of {Cortical} {Potential} {Using} {Realistic} {Models} of {Head} {Geometry}},
volume = {59},
number = {99},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Deng, S. and Winter, W. and Thorpe, S. and Srinivasan, R.},
year = {2012},
pages = {2979 --2985}
}
@article{wolpaw_braincomputer_2002,
title = {Brain–computer interfaces for communication and control},
volume = {113},
url = {http://www.sciencedirect.com/science/article/pii/S1388245702000573},
number = {6},
urldate = {2016-04-12},
journal = {Clinical neurophysiology},
author = {Wolpaw, Jonathan R. and Birbaumer, Niels and McFarland, Dennis J. and Pfurtscheller, Gert and Vaughan, Theresa M.},
year = {2002},
pages = {767--791},
file = {[HTML] from clinph-journal.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/EK7S2AN5/abstract.html:text/html;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/TMQ5DIXV/S1388245702000573.html:text/html}
}
@techreport{kalunga_using_2015,
title = {Using {Riemannian} geometry for {SSVEP}-based {Brain} {Computer} {Interface}},
url = {http://arxiv.org/abs/1501.03227},
institution = {Tshwane University of Technology \& Université de Versailles Saint-Quentin},
author = {Kalunga, Emmanuel K. and Chevallier, Sylvain and Barthélemy, Quentin},
year = {2015}
}
@article{kang_composite_2009,
title = {Composite common spatial pattern for subject-to-subject transfer},
volume = {16},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4912345},
number = {8},
urldate = {2016-06-01},
journal = {Signal Processing Letters, IEEE},
author = {Kang, Hyohyeong and Nam, Yunjun and Choi, Seungjin},
year = {2009},
pages = {683--686},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/4IIEG6DQ/login.html:text/html}
}
@article{schalk_brain-computer_2011,
title = {Brain-computer interfaces using electrocorticographic signals},
volume = {4},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6047564},
urldate = {2016-04-15},
journal = {Biomedical Engineering, IEEE Reviews in},
author = {Schalk, Gerwin and Leuthardt, Eric C.},
year = {2011},
pages = {140--154},
file = {[PDF] à partir de neurotechcenter.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/3VW44WIF/Schalk and Leuthardt - 2011 - Brain-computer interfaces using electrocorticograp.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/R787D776/login.html:text/html}
}
@inproceedings{raina_self-taught_2007,
title = {Self-taught learning: transfer learning from unlabeled data},
booktitle = {{ICML} '07: {Proceedings} of the 24th international conference on {Machine} learning},
publisher = {ACM},
author = {Raina, R. and Battle, A. and Lee, H. and Packer, B. and Ng, A.Y.},
year = {2007},
pages = {759--766}
}
@article{shenoy_towards_2006,
title = {Towards adaptive classification for {BCI}},
volume = {3},
number = {1},
journal = {Journal of Neural Engineering},
author = {Shenoy, Pradeep and Krauledat, Matthias and Blankertz, Benjamin and Rao, Rajesh P. N. and Müller, Klaus-Robert},
month = mar,
year = {2006},
pages = {R13+}
}
@incollection{verschore_dynamic_2012,
title = {Dynamic stopping improves the speed and accuracy of a {P}300 speller},
booktitle = {Artificial {Neural} {Networks} and {Machine} {Learning}–{ICANN} 2012},
publisher = {Springer},
author = {Verschore, Hannes and Kindermans, Pieter-Jan and Verstraeten, David and Schrauwen, Benjamin},
year = {2012},
pages = {661--668}
}
@article{hardoon_canonical_2004,
title = {Canonical {Correlation} {Analysis}: {An} {Overview} with {Application} to {Learning} {Methods}},
volume = {16},
number = {12},
journal = {Neural Comput.},
author = {Hardoon, David R. and Szedmak, Sandor R. and Shawe-Taylor, John R.},
year = {2004},
pages = {2639--2664}
}
@article{sun_-line_2010,
title = {On-line {EEG} classification for brain-computer interface based on {CSP} and {SVM}},
volume = {9},
journal = {Image and Signal Processing (CISP), 2010 3rd International Congress on},
author = {Sun, Hongyu and Xiang, Yang and Sun, Yaoru and Zhu, Huaping and {Jinhua Zeng}},
year = {2010},
pages = {4105--4108}
}
@article{jrad_sw-svm:_2011,
title = {sw-{SVM}: sensor weighting support vector machines for {EEG}-based brain-computer interfaces},
volume = {8},
number = {5},
journal = {Journal of Neural Engineering},
author = {Jrad, N. and Congedo, M. and Phlypo, R. and Rousseau, S. and Flamary, R. and Yger, F. and Rakotomamonjy, A.},
year = {2011},
pages = {056004}
}
@article{pencina_evaluating_2008,
title = {Evaluating the added predictive ability of a new marker: from area under the {ROC} curve to reclassification and beyond},
volume = {27},
number = {2},
journal = {Statistics in medicine},
author = {Pencina, Michael J and D'Agostino, Ralph B and Vasan, Ramachandran S},
year = {2008},
pages = {157--172}
}
@incollection{krizhevsky_imagenet_2012,
title = {{ImageNet} {Classification} with {Deep} {Convolutional} {Neural} {Networks}},
booktitle = {Advances in {Neural} {Information} {Processing} {Systems} 25},
author = {Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E.},
editor = {Pereira, F. and Burges, C. J. C. and Bottou, L. and Weinberger, K. Q.},
year = {2012},
pages = {1097--1105}
}
@article{caton_electrical_1875,
title = {Electrical {Currents} of the {Brain}.},
volume = {2},
url = {http://journals.lww.com/jonmd/Citation/1875/10000/Electrical_Currents_of_the_Brain.13.aspx},
number = {4},
urldate = {2016-04-15},
journal = {The Journal of Nervous and Mental Disease},
author = {Caton, Richard},
year = {1875},
pages = {610},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/RMHS4N4H/Electrical_Currents_of_the_Brain.13.html:text/html}
}
@article{johannes_designing_1999,
title = {Designing optimal spatial filters for single-trial {EEG} classification in a movement task},
volume = {110},
number = {5},
journal = {Clinical Neurophysiology},
author = {Johannes, Muller-Gerking and Pfurtscheller, Gert and Flyvbjerg, Henrik},
year = {1999},
pages = {787--798}
}
@article{pfurtscheller_self-paced_2010,
title = {Self-{Paced} {Operation} of an {SSVEP}-{Based} {Orthosis} {With} and {Without} an {Imagery}-{Based} {Brain} {Switch}: {A} {Feasibility} {Study} {Towards} a {Hybrid} {BCI}},
volume = {18},
number = {4},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {Pfurtscheller, G. and Solis-Escalante, T. and Ortner, R. and Linortner, P. and Muller-Putz, G.R.},
year = {2010},
pages = {409--414}
}
@article{blankertz_bci_2006,
title = {The {BCI} competition {III}: validating alternative approaches to actual {BCI} problems},
volume = {14},
number = {2},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {Blankertz, B. and Muller, K.-R. and Krusienski, D.J. and Schalk, G. and Wolpaw, J.R. and Schlogl, A. and Pfurtscheller, G. and Millan, Jd.R. and Schroder, M. and Birbaumer, N.},
year = {2006},
pages = {153--159}
}
@article{li_riemannian_2013,
title = {Riemannian {Distances} for {Signal} {Classification} by {Power} {Spectral} {Density}},
volume = {7},
number = {4},
journal = {Selected Topics in Signal Processing, IEEE Journal of},
author = {Li, Yili and Wong, K. M.},
year = {2013},
pages = {655--669}
}
@article{bashashati_survey_2007,
title = {A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals},
volume = {4},
number = {2},
journal = {journal of neural engineering},
author = {Bashashati, A. and Fatourechi, M and Ward, RK and Birch, GE},
year = {2007}
}
@article{ting_eeg_2008,
title = {{EEG} feature extraction based on wavelet packet decomposition for brain computer interface},
volume = {41},
number = {6},
journal = {Measurement},
author = {Ting, Wu and Guo-zheng, Yan and Bang-hua, Yang and Hong, Sun},
year = {2008},
pages = {618--625}
}
@article{chen_adaptive_2010,
title = {An {Adaptive} {Feature} {Extraction} {Method} for {Motor}-{Imagery} {BCI} {Systems}},
journal = {Computational Intelligence and Security (CIS), 2010 International Conference on},
author = {Chen, Cheng and Song, Wei and Zhang, Jiacai and Hu, Zhiping and Xu, He},
year = {2010},
pages = {275--279}
}
@article{muller_feature-selective_2006,
title = {Feature-selective attention enhances color signals in early visual areas of the human brain},
volume = {103},
issn = {0027-8424},
doi = {10.1073/pnas.0606668103},
abstract = {We used an electrophysiological measure of selective stimulus processing (the steady-state visual evoked potential, SSVEP) to investigate feature-specific attention to color cues. Subjects viewed a display consisting of spatially intermingled red and blue dots that continually shifted their positions at random. The red and blue dots flickered at different frequencies and thereby elicited distinguishable SSVEP signals in the visual cortex. Paying attention selectively to either the red or blue dot population produced an enhanced amplitude of its frequency-tagged SSVEP, which was localized by source modeling to early levels of the visual cortex. A control experiment showed that this selection was based on color rather than flicker frequency cues. This signal amplification of attended color items provides an empirical basis for the rapid identification of feature conjunctions during visual search, as proposed by "guided search" models.},
language = {eng},
number = {38},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
author = {Müller, M. M. and Andersen, S. and Trujillo, N. J. and Valdés-Sosa, P. and Malinowski, P. and Hillyard, S. A.},
month = sep,
year = {2006},
pmid = {16956975},
pmcid = {PMC1599943},
keywords = {Adult, Attention, Behavior, Brain Mapping, Color, Color Perception, Evoked Potentials, Visual, Female, Form Perception, Humans, Photic Stimulation, Random Allocation},
pages = {14250--14254}
}
@article{trad_nonlinear_2011,
title = {Nonlinear and nonstationary framework for feature extraction and classification of motor imagery},
journal = {Rehabilitation Robotics (ICORR), 2011 IEEE International Conference on},
author = {Trad, D. and Al-ani, T. and Monacelli, E. and Jemni, M.},
year = {2011},
pages = {1--6}
}
@article{kanal_dimensionality_1971,
title = {On dimensionality and sample size in statistical pattern classification},
volume = {3},
url = {http://www.sciencedirect.com/science/article/pii/0031320371900136},
number = {3},
urldate = {2016-05-29},
journal = {Pattern recognition},
author = {Kanal, Laveen and Chandrasekaran, B.},
year = {1971},
pages = {225--234},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BDU5U3W7/0031320371900136.html:text/html}
}
@inproceedings{chen_eeg-based_2012,
title = {An {EEG}-based brain?computer interface with real-time artifact removal using independent component analysis},
booktitle = {Consumer {Electronics}-{Berlin} ({ICCE}-{Berlin}), 2012 {IEEE} {International} {Conference} on},
publisher = {IEEE},
author = {Chen, Chiu-Kuo and Chua, E and Hsieh, Zong-Han and Fang, Wai-Chi and Wang, Yu-Te and Jung, Tzyy-Ping},
year = {2012},
pages = {13--14}
}
@article{bin_online_2009,
title = {An online multi-channel {SSVEP}-based brain-computer interface using a canonical correlation analysis method},
volume = {6},
number = {4},
journal = {Journal of Neural Engineering},
author = {Bin, G. and Gao, X. and Yan, Z. and Hong, B. and Gao, S.},
year = {2009}
}
@article{kaper_bci_2004,
title = {{BCI} competition 2003-data set {IIb}: support vector machines for the {P}300 speller paradigm},
volume = {51},
number = {6},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Kaper, M. and Meinicke, P. and Grossekathoefer, U. and Lingner, T. and Ritter, H.},
year = {2004},
pages = {1073--1076}
}
@article{donchin_mental_2000,
title = {The mental prosthesis: assessing the speed of a {P}300-based brain-computer interface},
volume = {8},
number = {2},
journal = {Rehabilitation Engineering, IEEE Transactions on [see also IEEE Trans. on Neural Systems and Rehabilitation]},
author = {Donchin, E. and Spencer, K. M. and Wijesinghe, R.},
year = {2000}
}
@inproceedings{gaur_empirical_2015,
title = {An empirical mode decomposition based filtering method for classification of motor-imagery {EEG} signals for enhancing brain-computer interface},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7280754},
urldate = {2016-05-11},
booktitle = {Neural {Networks} ({IJCNN}), 2015 {International} {Joint} {Conference} on},
publisher = {IEEE},
author = {Gaur, Pramod and Pachori, Ram Bilas and Wang, Hui and Prasad, Girijesh},
year = {2015},
pages = {1--7},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/G3GND845/login.html:text/html}
}
@article{millan_invasive_2010,
title = {Invasive or noninvasive: understanding brain-machine interface technology},
volume = {29},
shorttitle = {Invasive or noninvasive},
url = {http://infoscience.epfl.ch/record/150426/files/embs-mag_10.pdf},
number = {EPFL-ARTICLE-150426},
urldate = {2016-05-30},
journal = {IEEE Engineering in Medicine and Biology Magazine},
author = {Millán, José del R. and Carmena, J.},
year = {2010},
pages = {16--22},
file = {[PDF] from epfl.ch:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/XUHQC3B8/Millán and Carmena - 2010 - Invasive or noninvasive understanding brain-machi.pdf:application/pdf}
}
@book{hamdy_applied_2008,
title = {Applied signal processing: concepts, circuits, and systems},
isbn = {978-1-4200-6702-6},
publisher = {CRC Press/Taylor \& Francis},
author = {Hamdy, N.},
year = {2008}
}
@book{begg_computational_2007,
title = {Computational {Intelligence} in {Biomedical} {Engineering}},
isbn = {978-0-8493-4080-2},
publisher = {Taylor \& Francis},
author = {Begg, R. and Lai, D.T.H. and Palaniswami, M.},
year = {2007}
}
@article{kennedy_restoration_1998,
title = {Restoration of neural output from a paralyzed patient by a direct brain connection},
volume = {9},
url = {http://journals.lww.com/neuroreport/Abstract/1998/06010/Restoration_of_neural_output_from_a_paralyzed.7.aspx},
number = {8},
urldate = {2016-04-17},
journal = {Neuroreport},
author = {Kennedy, P. R. and Bakay, R. AE},
year = {1998},
pages = {1707--1711},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/XEQ5Q2HR/Restoration_of_neural_output_from_a_paralyzed.7.html:text/html}
}
@article{blankertz_optimizing_2008,
title = {Optimizing {Spatial} filters for {Robust} {EEG} {Single}-{Trial} {Analysis}},
volume = {25},
abstract = {Due to the volume conduction multichannel electroencephalogram (EEG) recordings give a rather blurred image of brain activity. Therefore spatial filters are extremely useful in single-trial analysis in order to improve the signal-to-noise ratio. There are powerful methods from machine learning and signal processing that permit the optimization of spatio-temporal filters for each subject in a data dependent fashion beyond the fixed filters based on the sensor geometry, e.g., Laplacians. Here we elucidate the theoretical background of the common spatial pattern (CSP) algorithm, a popular method in brain-computer interface (BCD research. Apart from reviewing several variants of the basic algorithm, we reveal tricks of the trade for achieving a powerful CSP performance, briefly elaborate on theoretical aspects of CSP, and demonstrate the application of CSP-type preprocessing in our studies of the Berlin BCI (BBCI) project.},
number = {1},
journal = {Signal Processing Magazine, IEEE},
author = {Blankertz, B. and Tomioka, R. and Lemm, S. and Kawanabe, M. and Muller, K. R.},
year = {2008},
pages = {41--56}
}
@book{scholkopf_learning_2001,
title = {Learning with kernels: support vector machines, regularization, optimization, and beyond},
shorttitle = {Learning with kernels},
url = {http://dl.acm.org/citation.cfm?id=559923},
urldate = {2016-06-01},
publisher = {MIT press},
author = {Scholkopf, Bernhard and Smola, Alexander J.},
year = {2001},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/EHGEN7SE/citation.html:text/html}
}
@article{rossion_n170_2000,
title = {The {N}170 occipito-temporal component is delayed and enhanced to inverted faces but not to inverted objects: an electrophysiological account of face-specific processes in the human brain},
volume = {11},
shorttitle = {The {N}170 occipito-temporal component is delayed and enhanced to inverted faces but not to inverted objects},
url = {http://journals.lww.com/neuroreport/Abstract/2000/01170/The_N170_occipito_temporal_component_is_delayed.14.aspx},
number = {1},
urldate = {2016-02-01},
journal = {Neuroreport},
author = {Rossion, Bruno and Gauthier, Isabel and Tarr, M. J. and Despland, P. and Bruyer, Raymond and Linotte, S. and Crommelinck, Marc},
year = {2000},
pages = {69--72},
file = {[PDF] à partir de researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/UHDQKS3G/Rossion et al. - 2000 - The N170 occipito-temporal component is delayed an.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/N89Q8S9B/The_N170_occipito_temporal_component_is_delayed.14.html:text/html}
}
@article{dellon_prosthetics_2007,
title = {Prosthetics, exoskeletons, and rehabilitation [{Grand} {Challenges} of {Robotics}]},
volume = {14},
abstract = {The paper briefly discusses the history of artificial limbs and describes present prosthetics, exoskeletons and robotic rehabilitation. The challenges in prosthetics and exoskeletons - which include electromechanical implementation, neural control signals and extraction of intent, and clinical interface - are also discussed. In the future, the need for assistive robotic devices is predicted to increase},
number = {1},
journal = {Robotics \& Automation Magazine, IEEE},
author = {Dellon, B. and Matsuoka, Y.},
year = {2007},
pages = {30--34}
}
@article{pastor_human_2003,
title = {Human cerebral activation during steady-state visual-evoked responses},
volume = {23},
number = {37},
journal = {The Journal of Neuroscience},
author = {Pastor, Maria A.},
year = {2003},
pages = {11621--11627}
}
@article{comon_independent_1994,
title = {Independent component analysis, a new concept?},
volume = {36},
number = {3},
journal = {Signal Process.},
author = {Comon, Pierre},
year = {1994},
pages = {287--314}
}
@article{wolpaw_eeg-based_1991,
title = {An {EEG}-based brain-computer interface for cursor control},
volume = {78},
number = {3},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Wolpaw, Jonathan R. and McFarland, Dennis J. and Neat, Gregory W. and Forneris, Catherine A.},
year = {1991},
pages = {252--259}
}
@article{ferrez_simultaneous_2008,
title = {Simultaneous {Real}-{Time} {Detection} of {Motor} {Imagery} and {Error}-{Related} {Potentials} for {Improved} {BCI} {Accuracy}},
journal = {Proceedings of the 4th International Brain-Computer Interface Workshop and Training Course},
author = {Ferrez, P. W. and Millan, J. del R.},
year = {2008},
pages = {197--202}
}
@inproceedings{barachant_channel_2011,
title = {Channel selection procedure using {Riemannian} distance for {BCI} applications},
booktitle = {Neural {Engineering} ({NER}), 2011 5th {International} {IEEE}/{EMBS} {Conference} on},
publisher = {IEEE},
author = {Barachant, Alexandre and Bonnet, Stéphane},
year = {2011},
pages = {348--351}
}
@article{daly_brain-computer_2008,
title = {Brain-{Computer} interfaces in neurological rehabilitation},
volume = {7},
number = {11},
journal = {The Lancet Neurology},
author = {Daly, Janis J. and Wolpaw, Jonathan R.},
year = {2008},
pages = {1032--1043}
}
@misc{team_elekta_????,
title = {Elekta {Neuromag}® {TRIUX}™ {Functional} {Mapping}},
url = {https://www.elekta.com/diagnostic-solutions/elekta-neuromag-triux.html},
abstract = {Elekta Neuromag TRIUX with internal helium recycler is the latest generation MEG system.},
urldate = {2016-05-31},
journal = {Elekta AB},
author = {Team, Elekta Web},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/P53B7KA6/elekta-neuromag-triux.html:text/html}
}
@article{fisher_photic-_2005,
title = {Photic- and pattern-induced seizures: a review for the {Epilepsy} {Foundation} of {America} {Working} {Group}},
volume = {46},
issn = {0013-9580},
shorttitle = {Photic- and pattern-induced seizures},
doi = {10.1111/j.1528-1167.2005.31405.x},
abstract = {PURPOSE: This report summarizes background material presented to a consensus conference on visually provoked seizures, convened by the Epilepsy Foundation of America.
METHODS: A comprehensive review of literature was performed.
RESULTS: Photosensitivity, an abnormal EEG response to light or pattern stimulation, occurs in approximately 0.3-3\% of the population. The estimated prevalence of seizures from light stimuli is approximately 1 per 10,000, or 1 per 4,000 individuals age 5-24 years. People with epilepsy have a 2-14\% chance of having seizures precipitated by light or pattern. In the Pokemon cartoon incident in Japan, 685 children visited a hospital in reaction to red-blue flashes on broadcast television (TV). Only 24\% who had a seizure during the cartoon had previously experienced a seizure. Photic or pattern stimulation can provoke seizures in predisposed individuals, but such stimulation is not known to increase the chance of subsequent epilepsy. Intensities of 0.2-1.5 million candlepower are in the range to trigger seizures. Frequencies of 15-25 Hz are most provocative, but the range is 1-65 Hz. Light-dark borders can induce pattern-sensitive seizures, and red color also is a factor. Seizures can be provoked by certain TV shows, movie screen images, video games, natural stimuli (e.g, sun on water), public displays, and many other sources.
CONCLUSIONS: Recommendations on reducing risk of seizures have been developed by agencies in the United Kingdom, Japan, and the International Telecommunications Union, affiliated with the United Nations. The Epilepsy Foundation of America has developed a consensus of medical experts and scientists on this subject, reported in an accompanying work.},
language = {eng},
number = {9},
journal = {Epilepsia},
author = {Fisher, Robert S. and Harding, Graham and Erba, Giuseppe and Barkley, Gregory L. and Wilkins, Arnold and {Epilepsy Foundation of America Working Group}},
month = sep,
year = {2005},
pmid = {16146439},
keywords = {Cartoons as Topic, Computer Terminals, Epilepsy, Reflex, Light, Pattern Recognition, Visual, Photic Stimulation, Television, United States},
pages = {1426--1441}
}
@article{kloth_combined_2013,
title = {Combined effects of inversion and feature removal on {N}170 responses elicited by faces and car fronts},
volume = {81},
issn = {02782626},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0278262613000031},
doi = {10.1016/j.bandc.2013.01.002},
language = {en},
number = {3},
urldate = {2016-02-01},
journal = {Brain and Cognition},
author = {Kloth, Nadine and Itier, Roxane J. and Schweinberger, Stefan R.},
month = apr,
year = {2013},
pages = {321--328},
file = {[HTML] from nih.gov:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/NCU86SVU/PMC3926862.html:text/html;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/XF9FKSUF/S0278262613000031.html:text/html}
}
@inproceedings{kalunga_data_2015,
title = {Data augmentation in {Riemannian} space for {Brain}-{Computer} {Interfaces}},
url = {https://hal.inria.fr/hal-01225255/},
urldate = {2016-05-31},
booktitle = {{ICML} {Workshop} on {Statistics}, {Machine} {Learning} and {Neuroscience} ({Stamlins} 2015)},
author = {Kalunga, Emmanuel and Chevallier, Sylvain and Barthélemy, Quentin},
year = {2015},
file = {[PDF] from inria.fr:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BII45ZHR/Kalunga et al. - 2015 - Data augmentation in Riemannian space for Brain-Co.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/8CW8HVM3/hal-01225255.html:text/html}
}
@article{roland_supplementary_1980,
title = {Supplementary motor area and other cortical areas in organization of voluntary movements in man},
volume = {43},
number = {1},
journal = {Neurophysiology},
author = {Roland, P. and Larsen, B. and Lassen, N. and Skinhoj, E.},
year = {1980},
pages = {118--136}
}
@article{morgan_selective_1996,
title = {Selective attention to stimulus location modulates the steady-state visual evoked potential},
volume = {93},
url = {http://www.pnas.org/content/93/10/4770.short},
number = {10},
urldate = {2016-05-02},
journal = {Proceedings of the National Academy of Sciences},
author = {Morgan, S. T. and Hansen, J. C. and Hillyard, S. A.},
year = {1996},
pages = {4770--4774},
file = {[PDF] from pnas.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/X4NFKEPR/Morgan et al. - 1996 - Selective attention to stimulus location modulates.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/TA2HRWUB/4770.html:text/html}
}
@article{sagiv_structural_2001,
title = {Structural encoding of human and schematic faces: holistic and part-based processes},
volume = {13},
shorttitle = {Structural encoding of human and schematic faces},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6789850},
number = {7},
urldate = {2016-02-01},
journal = {Cognitive Neuroscience, Journal of},
author = {Sagiv, Noam and Bentin, Shlomo},
year = {2001},
pages = {937--951},
file = {[PDF] from huji.ac.il:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/HZ46R52G/Sagiv and Bentin - 2001 - Structural encoding of human and schematic faces .pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/9DWUAF3V/login.html:text/html}
}
@article{sitaram_fmri_2008,
title = {{fMRI} {Brain}-{Computer} {Interfaces}},
volume = {25},
issn = {1053-5888},
doi = {10.1109/MSP.2008.4408446},
abstract = {Brain-computer interfaces based on fMRI enable real-time feedback of circumscribed brain regions to learn volitional regulation of those regions. This is an emerging field of intense research, with potential for multiple applications in neuroscientific research in brain plasticity and reorganization, movement restoration due to stroke, clinical rehabilitation of emotional disorders, quality assurance of fMRI experiments, and teaching functional imaging. This article presents a general architecture of an fMRI-BCI, with descriptions of each of its subsystems, and factors influencing their performance. The study has attempted to describe and compare a variety of approaches toward signal acquisition, preprocessing, analysis, and feedback. Technological advancement in higher-field MRI scanners, data acquisition sequences and image reconstruction techniques, preprocessing algorithms to correct for artifacts, more intelligent and robust analysis and interpretation methods, and faster feedback and visualization technology are anticipated to make fMRI-BCI widely applicable. FMRI-BCI could potentially be used for training patients to learn self-regulation of specific brain areas for transferring them later on to a more portable EEG-BCI system. FMRI-BCI has the potential of establishing itself as a tool for neuroscientific research and experimentation and also as an aid for psychophysiological treatment.},
number = {1},
journal = {IEEE Signal Processing Magazine},
author = {Sitaram, R. and Weiskopf, N. and Caria, A. and Veit, R. and Erb, M. and Birbaumer, N.},
year = {2008},
keywords = {artifact correction, biomechanics, biomedical MRI, Brain, brain-computer interfaces, brain computer interfaces, brain plasticity, brain reorganization, circumscribed brain regions, clinical rehabilitation, data acquisition, diseases, Education, EEG-BCI system, emotional disorders, feedback, fMRI, functional imaging, higher-field MRI scanners, image reconstruction, Image restoration, learning, learning (artificial intelligence), Magnetic resonance imaging, medical signal processing, movement restoration, Neurofeedback, neurophysiology, Neuroplasticity, neuroscientific research, patient rehabilitation, patient training, patient treatment, plasticity, psychology, psychophysiological treatment, quality assurance, real-time feedback, signal acquisition, Signal analysis, signal preprocessing, stroke, user interfaces, visualization technology, volitional regulation},
pages = {95--106},
file = {IEEE Xplore Abstract Record:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BQVXBFVG/login.html:text/html}
}
@inproceedings{barbaresco_geometric_2011,
title = {Geometric radar processing based on {Fréchet} distance: information geometry versus optimal transport theory},
shorttitle = {Geometric radar processing based on {Fréchet} distance},
url = {https://www.infona.pl/resource/bwmeta1.element.ieee-art-000006042179},
urldate = {2016-03-17},
booktitle = {2011 12th {International} {Radar} {Symposium} ({IRS})},
author = {Barbaresco, Frédéric},
year = {2011},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/95QJ6KF5/bwmeta1.element.html:text/html}
}
@misc{_search_????,
title = {Search results - [email protected] - {Gmail}},
url = {https://mail.google.com/mail/u/0/?tab=wm#search/ismailawatt%40gmail.com?compose=14e529c865b2b0f3},
urldate = {2015-07-03},
file = {Search results - [email protected] - Gmail:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/GVNNZSTR/0.html:text/html}
}
@article{alhaddad_p300_2012,
title = {P300 speller efficiency with common average reference},
journal = {Proceedings of the Third International conference on Autonomous and Intelligent Systems},
author = {Alhaddad, Mohammed J. and Kamel, Mahmoud and Malibary, Hussein and Thabit, Khalid and Dahlwi, Foud and Hadi, Anas},
year = {2012},
pages = {234--241}
}
@article{mcfarland_bci_2006-1,
title = {{BCI} meeting 2005-workshop on {BCI} signal processing: feature extraction and translation},
volume = {14},
shorttitle = {{BCI} meeting 2005-workshop on {BCI} signal processing},
url = {https://www.researchgate.net/profile/Dennis_Mcfarland2/publication/6992727_BCI_Meeting_2005--workshop_on_BCI_signal_processing_feature_extraction_and_translation/links/0deec5331d1835fd20000000.pdf},
number = {2},
urldate = {2016-05-11},
journal = {IEEE transactions on neural systems and rehabilitation engineering},
author = {McFarland, Dennis J. and Anderson, Charles W. and Muller, K. and Schlogl, Alois and Krusienski, Dean J.},
year = {2006},
pages = {135},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/B3V5ITTX/McFarland et al. - 2006 - BCI meeting 2005-workshop on BCI signal processing.pdf:application/pdf}
}
@article{kubler_severity_2005,
title = {Severity of depressive symptoms and quality of life in patients with amyotrophic lateral sclerosis},
volume = {19},
url = {http://nnr.sagepub.com/content/19/3/182.short},
number = {3},
urldate = {2016-04-21},
journal = {Neurorehabilitation and neural repair},
author = {Kübler, Andrea and Winter, Susanne and Ludolph, Albert C. and Hautzinger, Martin and Birbaumer, Niels},
year = {2005},
pages = {182--193},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/MW8CI9RI/182.html:text/html}
}
@article{chang_libsvm:_2011,
title = {{LIBSVM}: {A} {Library} for {Support} {Vector} {Machines}},
volume = {2},
number = {3},
journal = {ACM Trans. Intell. Syst. Technol.},
author = {Chang, Chih C. and Lin, Chih J.},
year = {2011}
}
@book{nunez_electric_2005,
edition = {2},
title = {Electric {Fields} of the {Brain}: {The} {Neurophysics} of {EEG}, 2nd {Edition}},
isbn = {0-19-505038-X},
publisher = {Oxford University Press, USA},
author = {Nunez, Paul L. and Srinivasan, Ramesh},
year = {2005}
}
@article{ferrari_brief_2012,
title = {A brief review on the history of human functional near-infrared spectroscopy ({fNIRS}) development and fields of application},
volume = {63},
issn = {10538119},
url = {http://linkinghub.elsevier.com/retrieve/pii/S1053811912003308},
doi = {10.1016/j.neuroimage.2012.03.049},
language = {en},
number = {2},
urldate = {2016-04-19},
journal = {NeuroImage},
author = {Ferrari, Marco and Quaresima, Valentina},
month = nov,
year = {2012},
pages = {921--935}
}
@article{zhang_comparison_2015,
title = {Comparison of classification methods on {EEG} signals based on wavelet packet decomposition},
volume = {26},
url = {http://link.springer.com/article/10.1007/s00521-014-1786-7},
number = {5},
urldate = {2016-05-12},
journal = {Neural Computing and Applications},
author = {Zhang, Yong and Zhang, Yuting and Wang, Jianying and Zheng, Xiaowei},
year = {2015},
pages = {1217--1225},
file = {[HTML] from springer.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ZZJTQB7I/fulltext.html:text/html;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/J64ZMK2Z/s00521-014-1786-7.html:text/html}
}
@incollection{barachant_riemannian_2010,
title = {Riemannian geometry applied to {BCI} classification},
booktitle = {Latent {Variable} {Analysis} and {Signal} {Separation}},
publisher = {Springer},
author = {Barachant, Alexandre and Bonnet, Stéphane and Congedo, Marco and Jutten, Christian},
year = {2010},
pages = {629--636}
}
@article{lee_pca+hmm+svm_2003,
title = {{PCA}+{HMM}+{SVM} for {EEG} pattern classification},
volume = {1},
journal = {Signal Processing and Its Applications, 2003. Proceedings. Seventh International Symposium on},
author = {Lee, Hyekyung and Choi, Seungjin},
year = {2003},
pages = {541--544}
}
@article{zander_towards_2011,
title = {Towards passive brain-computer interfaces: applying brain-computer interface technology to human-machine systems in general},
volume = {8},
issn = {1741-2552},
shorttitle = {Towards passive brain-computer interfaces},
doi = {10.1088/1741-2560/8/2/025005},
abstract = {Cognitive monitoring is an approach utilizing realtime brain signal decoding (RBSD) for gaining information on the ongoing cognitive user state. In recent decades this approach has brought valuable insight into the cognition of an interacting human. Automated RBSD can be used to set up a brain-computer interface (BCI) providing a novel input modality for technical systems solely based on brain activity. In BCIs the user usually sends voluntary and directed commands to control the connected computer system or to communicate through it. In this paper we propose an extension of this approach by fusing BCI technology with cognitive monitoring, providing valuable information about the users' intentions, situational interpretations and emotional states to the technical system. We call this approach passive BCI. In the following we give an overview of studies which utilize passive BCI, as well as other novel types of applications resulting from BCI technology. We especially focus on applications for healthy users, and the specific requirements and demands of this user group. Since the presented approach of combining cognitive monitoring with BCI technology is very similar to the concept of BCIs itself we propose a unifying categorization of BCI-based applications, including the novel approach of passive BCI.},
language = {eng},
number = {2},
journal = {Journal of Neural Engineering},
author = {Zander, Thorsten O. and Kothe, Christian},
month = apr,
year = {2011},
pmid = {21436512},
keywords = {Biofeedback, Psychology, Brain, Brain Mapping, Cognition, Electroencephalography, Forecasting, Humans, Man-Machine Systems, Signal Processing, Computer-Assisted, User-Computer Interface},
pages = {025005}
}
@book{hastie_elements_2009,
address = {New York, NY},
series = {Springer {Series} in {Statistics}},
title = {The {Elements} of {Statistical} {Learning}},
isbn = {978-0-387-84857-0 978-0-387-84858-7},
url = {http://link.springer.com/10.1007/978-0-387-84858-7},
urldate = {2016-06-23},
publisher = {Springer New York},
author = {Hastie, Trevor and Tibshirani, Robert and Friedman, Jerome},
year = {2009}
}
@article{falkenstein_erp_2000,
title = {{ERP} components on reaction errors and their functional significance: a tutorial},
volume = {51},
shorttitle = {{ERP} components on reaction errors and their functional significance},
url = {http://www.sciencedirect.com/science/article/pii/S0301051199000319},
number = {2},
urldate = {2016-04-28},
journal = {Biological psychology},
author = {Falkenstein, Michael and Hoormann, Jörg and Christ, Stefan and Hohnsbein, Joachim},
year = {2000},
pages = {87--107},
file = {[PDF] from sfu.ca:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/3ZFBIWSU/Falkenstein et al. - 2000 - ERP components on reaction errors and their functi.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/K96GRCE6/S0301051199000319.html:text/html}
}
@book{purves_neuroscience_2008,
edition = {4th edition},
title = {Neuroscience, {Fourth} {Edition}},
isbn = {978-0-87893-697-7},
abstract = {Neuroscience is a comprehensive textbook created primarily for medical, premedical, and undergraduate students. In a single concise and approachable volume, the text guides students through the challenges and excitement of this rapidly changing field. The book s length and accessibility of its writing are a successful combination that has proven to work equally well for medical students and in undergraduate neuroscience courses. Being both comprehensive and authoritative, the book is also appropriate for graduate and professional use.},
language = {English},
publisher = {Sinauer Associates, Inc.},
author = {Purves, Dale},
month = jul,
year = {2008}
}
@article{lei_common_2009,
title = {Common {Spatial} {Pattern} {Ensemble} {Classifier} and its {Application} in {Brain}-{Computer} {Interface}},
volume = {7},
number = {1},
journal = {Journal of electronic science and technology of China},
author = {Lei, Xu and Yang, Ping and Xu, Peng and Liu, Tie-Jun and Yao, De-Zhong},
year = {2009}
}
@article{jrad_sw-svm:_2011-1,
title = {sw-{SVM}: sensor weighting support vector machines for {EEG}-based brain–computer interfaces},
volume = {8},
journal = {Journal of Neural Engineering},
author = {Jrad, N. and Congedo, M. and Phlypo, R. and Rousseau, S. and Flamary, R. and Yger, F. and Rakotomamonjy, A.},
year = {2011},
pages = {056004+}
}
@article{dhillon_matrix_2007,
title = {Matrix nearness problems with {Bregman} divergences},
volume = {29},
url = {http://epubs.siam.org/doi/abs/10.1137/060649021},
number = {4},
urldate = {2016-06-23},
journal = {SIAM Journal on Matrix Analysis and Applications},
author = {Dhillon, Inderjit S. and Tropp, Joel A.},
year = {2007},
pages = {1120--1146},
file = {[PDF] from caltech.edu:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/34ZWGBRC/Dhillon and Tropp - 2007 - Matrix nearness problems with Bregman divergences.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/GTCS3KWQ/060649021.html:text/html}
}
@article{penny_eeg-based_2000,
title = {{EEG}-based communication: a pattern recognition approach},
volume = {8},
number = {2},
journal = {Rehabilitation Engineering, IEEE Transactions on},
author = {Penny, W.D. and Roberts, S.J. and Curran, E.A. and Stokes, M.J.},
year = {2000},
pages = {214--215}
}
@article{lee_pca-based_2002,
title = {{PCA}-based linear dynamical systems for multichannel {EEG} classification},
volume = {2},
journal = {Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on},
author = {Lee, Hyekyoung and Choi, Seungjin},
year = {2002},
pages = {745--749}
}
@article{arvaneh_spatially_2011,
title = {Spatially sparsed {Common} {Spatial} {Pattern} to improve {BCI} performance},
journal = {Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on},
author = {Arvaneh, M. and Guan, Cuntai and Ang, Kai Keng and Quek, Hiok Chai},
year = {2011},
pages = {2412--2415}
}
@article{van_dyk_art_2001,
title = {The art of data augmentation},
volume = {10},
number = {1},
journal = {Journal of Computational and Graphical Statistics},
author = {Van Dyk, David A and Meng, Xiao-Li},
year = {2001}
}
@article{pfurtscheller_current_2000,
title = {Current trends in {Graz} brain-computer interface ({BCI}) research},
volume = {8},
number = {2},
journal = {Rehabilitation Engineering, IEEE Transactions on},
author = {Pfurtscheller, G. and Neuper, C. and Guger, C. and Harkam, W. and Ramoser, H. and Schlogl, A. and Obermaier, B. and Pregenzer, M.},
year = {2000},
pages = {216--219}
}
@article{jeannerod_mental_1995,
title = {Mental imagery in the motor context},
volume = {33},
number = {11},
journal = {Neuropsychologia},
author = {Jeannerod, M.},
year = {1995},
pages = {1419--1432}
}
@article{huggins_detection_1999,
title = {Detection of event-related potentials for development of a direct brain interface},
volume = {16},
url = {http://journals.lww.com/clinicalneurophys/Abstract/1999/09000/Detection_of_Event_Related_Potentials_for.6.aspx},
number = {5},
urldate = {2016-04-15},
journal = {Journal of clinical neurophysiology},
author = {Huggins, Jane E. and Levine, Simon P. and BeMent, Spencer L. and Kushwaha, Ramesh K. and Schuh, Lori A. and Passaro, Erasmo A. and Rohde, Mitchell M. and Ross, Donald A. and Elisevich, Kost V. and Smith, Brien J.},
year = {1999},
pages = {448},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/TP9JDE6B/Detection_of_Event_Related_Potentials_for.6.html:text/html}
}
@article{silvoni_brain-computer_2011,
title = {Brain-computer interface in stroke: a review of progress},
volume = {42},
shorttitle = {Brain-computer interface in stroke},
url = {http://eeg.sagepub.com/content/42/4/245.short},
number = {4},
urldate = {2016-04-12},
journal = {Clinical EEG and Neuroscience},
author = {Silvoni, Stefano and Ramos-Murguialday, Ander and Cavinato, Marianna and Volpato, Chiara and Cisotto, Giulia and Turolla, Andrea and Piccione, Francesco and Birbaumer, Niels},
year = {2011},
pages = {245--252},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/54G4SVJH/Silvoni et al. - 2011 - Brain-computer interface in stroke a review of pr.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/FHZTERSW/245.html:text/html}
}
@article{palaniappan_autoregressive_2000,
title = {Autoregressive spectral analysis and model order selection criteria for {EEG} signals},
volume = {2},
journal = {TENCON 2000. Proceedings},
author = {Palaniappan, R. and Raveendran, P. and Nishida, S. and Saiwaki, N.},
year = {2000},
pages = {126--129}
}
@inproceedings{ciresan_multi-column_2012,
title = {Multi-column deep neural networks for image classification},
booktitle = {Computer {Vision} and {Pattern} {Recognition} ({CVPR}), 2012 {IEEE} {Conference} on},
publisher = {IEEE},
author = {Ciresan, Dan and Meier, Ueli and Schmidhuber, Jürgen},
year = {2012},
pages = {3642--3649}
}
@article{weiskopf_principles_2004,
title = {Principles of a brain-computer interface ({BCI}) based on real-time functional magnetic resonance imaging ({fMRI})},
volume = {51},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1300789},
number = {6},
urldate = {2016-04-19},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Weiskopf, Nikolaus and Mathiak, Klaus and Bock, Simon W. and Scharnowski, Frank and Veit, Ralf and Grodd, Wolfgang and Goebel, Rainer and Birbaumer, Niels},
year = {2004},
pages = {966--970},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/93WUW2DV/Weiskopf et al. - 2004 - Principles of a brain-computer interface (BCI) bas.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BDU5T6M2/login.html:text/html}
}
@article{lopez_evidences_2009,
title = {Evidences of cognitive effects over auditory steady-state responses by means of artificial neural networks and its use in brain–computer interfaces},
volume = {72},
number = {16-18},
journal = {Neurocomputing},
author = {Lopez, M. A. and Pomares, Hector and Pelayo, Francisco and Urquiza, Jose and Perez, Javier},
year = {2009},
pages = {3617--3623}
}
@article{ming_ica-svm_2010,
title = {{ICA}-{SVM} combination algorithm for identification of motor imagery potentials},
journal = {Computational Intelligence for Measurement Systems and Applications (CIMSA), 2010 IEEE International Conference on},
author = {Ming, Dong and Sun, Changcheng and Cheng, Longlong and Bai, Yanru and Liu, Xiuyun and An, Xingwei and Qi, Hongzhi and Wan, Baikun and {Yong Hu} and Luk, K.D.K.},
year = {2010},
pages = {92--96}
}
@misc{center_for_history_and_new_media_zotero_????,
title = {Zotero {Quick} {Start} {Guide}},
url = {http://zotero.org/support/quick_start_guide},
author = {{Center for History and New Media}}
}
@article{kaufmann_flashing_2011,
title = {Flashing characters with famous faces improves {ERP}-based brain–computer interface performance},
volume = {8},
url = {http://iopscience.iop.org/article/10.1088/1741-2560/8/5/056016/meta},
number = {5},
urldate = {2016-04-28},
journal = {Journal of neural engineering},
author = {Kaufmann, Tobias and Schulz, S. M. and Grünzinger, Claudia and Kübler, Andrea},
year = {2011},
pages = {056016},
file = {[PDF] from tobi-project.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ACUGDE5T/Kaufmann et al. - 2011 - Flashing characters with famous faces improves ERP.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/U9BGSNDW/meta.html:text/html}
}
@article{congedo_new_2013,
title = {A {New} {Generation} of {Brain}-{Computer} {Interface} {Based} on {Riemannian} {Geometry}},
journal = {arXiv preprint arXiv:1310.8115},
author = {Congedo, Marco and Barachant, Alexandre and Andreev, Anton},
year = {2013}
}
@article{wolpaw_control_2004,
title = {Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans},
volume = {101},
url = {http://www.pnas.org/content/101/51/17849.short},
number = {51},
urldate = {2016-04-21},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
author = {Wolpaw, Jonathan R. and McFarland, Dennis J.},
year = {2004},
pages = {17849--17854},
file = {[HTML] from pnas.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/F3E576ZD/17849.html:text/html;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/WI59A3D5/17849.html:text/html}
}
@article{navajas_uncovering_2013,
title = {Uncovering the {Mechanisms} of {Conscious} {Face} {Perception}: {A} {Single}-{Trial} {Study} of the {N}170 {Responses}},
volume = {33},
issn = {0270-6474, 1529-2401},
shorttitle = {Uncovering the {Mechanisms} of {Conscious} {Face} {Perception}},
url = {http://www.jneurosci.org/cgi/doi/10.1523/JNEUROSCI.1226-12.2013},
doi = {10.1523/JNEUROSCI.1226-12.2013},
language = {en},
number = {4},
urldate = {2016-02-01},
journal = {Journal of Neuroscience},
author = {Navajas, J. and Ahmadi, M. and Quian Quiroga, R.},
month = jan,
year = {2013},
pages = {1337--1343},
file = {[HTML] from jneurosci.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/4XFUXNPJ/1337.html:text/html;[PDF] from le.ac.uk:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BFM7HCMC/Navajas et al. - 2013 - Uncovering the Mechanisms of Conscious Face Percep.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/6986U855/1337.html:text/html}
}
@inproceedings{iturrate_single_2010,
title = {Single trial recognition of error-related potentials during observation of robot operation},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5627380},
urldate = {2016-02-11},
booktitle = {Engineering in {Medicine} and {Biology} {Society} ({EMBC}), 2010 {Annual} {International} {Conference} of the {IEEE}},
publisher = {IEEE},
author = {Iturrate, Inaki and Montesano, Luis and Minguez, Javier},
year = {2010},
pages = {4181--4184},
file = {[PDF] à partir de epfl.ch:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/79JE7PGE/Iturrate et al. - 2010 - Single trial recognition of error-related potentia.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/WKHPXXXE/login.html:text/html}
}
@article{rakotomamonjy_ensemble_2005,
title = {Ensemble of {SVMs} for improving brain-computer interface {P}300 speller performances},
journal = {15th International Conference on Artificial Neural Networks},
author = {Rakotomamonjy, A. and Guigue, V. and Mallet, G. and Alvarado, V.},
year = {2005},
pages = {45--50}
}
@article{barachant_classification_2013,
title = {Classification of covariance matrices using a {Riemannian}-based kernel for {BCI} applications},
volume = {112},
journal = {Neurocomputing},
author = {Barachant, Alexandre and Bonnet, Stéphane and Congedo, Marco and Jutten, Christian},
year = {2013},
pages = {172--178}
}
@article{cherian_riemannian_2015,
title = {Riemannian {Dictionary} {Learning} and {Sparse} {Coding} for {Positive} {Definite} {Matrices}},
url = {http://arxiv.org/abs/1507.02772},
urldate = {2016-02-18},
journal = {arXiv preprint arXiv:1507.02772},
author = {Cherian, Anoop and Sra, Suvrit},
year = {2015},
file = {[PDF] à partir de arxiv.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/CAXNTZTM/Cherian and Sra - 2015 - Riemannian Dictionary Learning and Sparse Coding f.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/A6CB594W/1507.html:text/html}
}
@article{he_learning_2009,
title = {Learning from {Imbalanced} {Data}},
volume = {21},
issn = {1041-4347},
doi = {10.1109/TKDE.2008.239},
abstract = {With the continuous expansion of data availability in many large-scale, complex, and networked systems, such as surveillance, security, Internet, and finance, it becomes critical to advance the fundamental understanding of knowledge discovery and analysis from raw data to support decision-making processes. Although existing knowledge discovery and data engineering techniques have shown great success in many real-world applications, the problem of learning from imbalanced data (the imbalanced learning problem) is a relatively new challenge that has attracted growing attention from both academia and industry. The imbalanced learning problem is concerned with the performance of learning algorithms in the presence of underrepresented data and severe class distribution skews. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles, algorithms, and tools to transform vast amounts of raw data efficiently into information and knowledge representation. In this paper, we provide a comprehensive review of the development of research in learning from imbalanced data. Our focus is to provide a critical review of the nature of the problem, the state-of-the-art technologies, and the current assessment metrics used to evaluate learning performance under the imbalanced learning scenario. Furthermore, in order to stimulate future research in this field, we also highlight the major opportunities and challenges, as well as potential important research directions for learning from imbalanced data.},
number = {9},
journal = {IEEE Transactions on Knowledge and Data Engineering},
author = {He, H. and Garcia, E. A.},
month = sep,
year = {2009},
keywords = {active learning, assessment metrics., classification, complex systems, cost-sensitive learning, data availability, data engineering, data mining, decision making, imbalanced data, Imbalanced learning, kernel-based learning, knowledge discovery, large-scale systems, learning, learning (artificial intelligence), networked systems, sampling methods},
pages = {1263--1284},
file = {IEEE Xplore Abstract Record:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/WIJ4PHT6/login.html:text/html}
}
@article{muller_machine_2004,
title = {Machine learning techniques for brain-computer interfaces},
journal = {Biomedical Engineering},
author = {Müller, K. R. and Krauledat, M. and Dornhege, G. and Curio, G. and Blankertz, B.},
year = {2004},
pages = {11--22}
}
@article{acqualagna_gaze-independent_2013,
title = {Gaze-independent {BCI}-spelling using rapid serial visual presentation ({RSVP})},
volume = {124},
issn = {1388-2457},
url = {http://www.sciencedirect.com/science/article/pii/S1388245713000606},
doi = {10.1016/j.clinph.2012.12.050},
abstract = {Objective
A Brain Computer Interface (BCI) speller is a communication device, which can be used by patients suffering from neurodegenerative diseases to select symbols in a computer application. For patients unable to overtly fixate the target symbol, it is crucial to develop a speller independent of gaze shifts. In the present online study, we investigated rapid serial visual presentation (RSVP) as a paradigm for mental typewriting.
Methods
We investigated the RSVP speller in three conditions, regarding the Stimulus Onset Asynchrony (SOA) and the use of color features. A vocabulary of 30 symbols was presented one-by-one in a pseudo random sequence at the same location of display.
Results
All twelve participants were able to successfully operate the RSVP speller. The results show a mean online spelling rate of 1.43 symb/min and a mean symbol selection accuracy of 94.8\% in the best condition.
Conclusion
We conclude that the RSVP is a promising paradigm for BCI spelling and its performance is competitive with the fastest gaze-independent spellers in literature.
Significance
The RSVP speller does not require gaze shifts towards different target locations and can be operated by non-spatial visual attention, therefore it can be considered as a valid paradigm in applications with patients for impaired oculo-motor control.},
number = {5},
urldate = {2016-04-28},
journal = {Clinical Neurophysiology},
author = {Acqualagna, Laura and Blankertz, Benjamin},
month = may,
year = {2013},
keywords = {brain computer interfaces, ERPs, RSVP, Speller},
pages = {901--908},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/6A22RJX6/Acqualagna and Blankertz - 2013 - Gaze-independent BCI-spelling using rapid serial v.pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/T8R2N8ES/S1388245713000606.html:text/html}
}
@inproceedings{yger_review_2013,
title = {A review of kernels on covariance matrices for {BCI} applications},
booktitle = {Machine {Learning} for {Signal} {Processing} ({MLSP}), 2013 {IEEE} {International} {Workshop} on},
publisher = {IEEE},
author = {Yger, Florian},
year = {2013},
pages = {1--6}
}
@article{polich_p300_1991,
title = {P300 in the evaluation of aging and dementia},
volume = {42},
journal = {Electroencephalogr Clin Neurophysiol Suppl},
author = {Polich, J.},
year = {1991},
pages = {304--23}
}
@article{ren_idle_2008,
title = {Idle {State} {Detection} in {SSVEP}-{Based} {Brain}-{Computer} {Interfaces}},
journal = {Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on},
author = {Ren, R. and Bin, Guangyu and Gao, Xiaorong},
month = may,
year = {2008},
pages = {2012--2015}
}
@article{satti_a._and_coyle_d._and_prasad_g._continuous_2009,
title = {Continuous {EEG} classification for a self-paced {BCI}},
journal = {Neural Engineering, 2009. 4th International IEEE/EMBS Conference on},
author = {{Satti, A. and Coyle, D. and Prasad, G.}},
year = {2009},
pages = {315--318}
}
@article{huang_feature_2010,
title = {Feature extraction and classification of {EEG} for imagery movement based on mu/beta rhythms},
volume = {2},
journal = {Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on},
author = {Huang, Sijuan and Wu, Xiaoming},
year = {2010},
pages = {891--894}
}
@inproceedings{samek_information_2014,
title = {Information geometry meets {BCI} spatial filtering using divergences},
booktitle = {Brain-{Computer} {Interface} ({BCI}), 2014 {International} {Winter} {Workshop} on},
publisher = {IEEE},
author = {Samek, Wojciech and Muller, Klaus-Robert},
year = {2014},
pages = {1--4}
}
@article{chavarriaga_learning_2010,
title = {Learning from {EEG} error-related potentials in noninvasive brain-computer interfaces},
volume = {18},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5491194},
number = {4},
urldate = {2016-02-11},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {Chavarriaga, Ricardo and Millán, José del R.},
year = {2010},
pages = {381--388},
file = {[PDF] à partir de epfl.ch:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/IU2SH3J9/Chavarriaga and Millán - 2010 - Learning from EEG error-related potentials in noni.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/K2X9U4ZM/login.html:text/html}
}
@article{kathner_effects_2014,
title = {Effects of mental workload and fatigue on the {P}300, alpha and theta band power during operation of an {ERP} ({P}300) brain–computer interface},
volume = {102},
issn = {0301-0511},
url = {http://www.sciencedirect.com/science/article/pii/S0301051114001616},
doi = {10.1016/j.biopsycho.2014.07.014},
abstract = {The study aimed at revealing electrophysiological indicators of mental workload and fatigue during prolonged usage of a P300 brain–computer interface (BCI). Mental workload was experimentally manipulated with dichotic listening tasks. Medium and high workload conditions alternated. Behavioral measures confirmed that the manipulation of mental workload was successful. Reduced P300 amplitude was found for the high workload condition. Along with lower performance and an increase in the subjective level of fatigue, an increase of power in the alpha band was found for the last as compared to the first run of both conditions. The study confirms that a combination of signals derived from the time and frequency domain of the electroencephalogram is promising for the online detection of workload and fatigue. It also demonstrates that satisfactory accuracies can be achieved by healthy participants with the P300 speller, despite constant distraction and when pursuing the task for a long time.},
urldate = {2016-04-28},
journal = {Biological Psychology},
author = {Käthner, Ivo and Wriessnegger, Selina C. and Müller-Putz, Gernot R. and Kübler, Andrea and Halder, Sebastian},
month = oct,
year = {2014},
keywords = {Alpha, Brain–computer interface, EEG, Fatigue, Mental workload, P300},
pages = {118--129},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/TCQSBH98/Käthner et al. - 2014 - Effects of mental workload and fatigue on the P300.pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/K2FKGZB5/S0301051114001616.html:text/html}
}
@article{margaux_objective_2012,
title = {Objective and subjective evaluation of online error correction during {P}300-based spelling},
volume = {2012},
journal = {Advances in Human-Computer Interaction},
author = {Margaux, Perrin and Emmanuel, Maby and Sébastien, Daligault and Olivier, Bertrand and Jérémie, Mattout},
year = {2012},
pages = {4}
}
@article{lotte_regularizing_2011,
title = {Regularizing {Common} {Spatial} {Patterns} to {Improve} {BCI} {Designs}: {Unified} {Theory} and {New} {Algorithms}},
volume = {58},
number = {2},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Lotte, F. and Guan, Cuntai},
year = {2011},
pages = {355--362}
}
@article{fitzgerald_temporal_1967,
title = {Temporal and sequential probability in evoked potential studies},
volume = {35},
number = {2},
journal = {Canadian Journal of Psychology},
author = {Fitzgerald, Peter G. and Picton, Terence W.},
year = {1967},
pages = {188--200}
}
@inproceedings{lotte_generating_2011,
title = {Generating artificial {EEG} signals to reduce {BCI} calibration time},
booktitle = {5th {International} {Brain}-{Computer} {Interface} {Workshop}},
author = {Lotte, Fabien},
year = {2011},
pages = {176--179}
}
@incollection{kalunga_euclidean_2015,
series = {Lecture {Notes} in {Computer} {Science}},
title = {From {Euclidean} to {Riemannian} {Means}: {Information} {Geometry} for {SSVEP} {Classification}},
copyright = {©2015 Springer International Publishing Switzerland},
isbn = {978-3-319-25039-7 978-3-319-25040-3},
shorttitle = {From {Euclidean} to {Riemannian} {Means}},
url = {http://link.springer.com/chapter/10.1007/978-3-319-25040-3_64},
abstract = {Brain Computer Interfaces (BCI) based on electroencephalography (EEG) rely on multichannel brain signal processing. Most of the state-of-the-art approaches deal with covariance matrices, and indeed Riemannian geometry has provided a substantial framework for developing new algorithms. Most notably, a straightforward algorithm such as Minimum Distance to Mean yields competitive results when applied with a Riemannian distance. This applicative contribution aims at assessing the impact of several distances on real EEG dataset, as the invariances embedded in those distances have an influence on the classification accuracy. Euclidean and Riemannian distances and means are compared both in term of quality of results and of computational load.},
language = {en},
number = {9389},
urldate = {2016-03-09},
booktitle = {Geometric {Science} of {Information}},
publisher = {Springer International Publishing},
author = {Kalunga, Emmanuel K. and Chevallier, Sylvain and Barthélemy, Quentin and Djouani, Karim and Hamam, Yskandar and Monacelli, Eric},
editor = {Nielsen, Frank and Barbaresco, Frédéric},
year = {2015},
note = {DOI: 10.1007/978-3-319-25040-3\_64},
keywords = {Algorithm Analysis and Problem Complexity, Artificial Intelligence (incl. Robotics), Brain- Computer Interfaces, Computer Graphics, Discrete Mathematics in Computer Science, Image Processing and Computer Vision, Information geometry, Pattern Recognition, Riemannian means, Steady State Visually Evoked Potentials},
pages = {595--604},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/VBN93RMP/10.html:text/html}
}
@inproceedings{rivet_theoretical_2011,
title = {Theoretical analysis of {xDAWN} algorithm: application to an efficient sensor selection in a {P}300 {BCI}},
shorttitle = {Theoretical analysis of {xDAWN} algorithm},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7073970},
urldate = {2016-05-24},
booktitle = {Signal {Processing} {Conference}, 2011 19th {European}},
publisher = {IEEE},
author = {Rivet, Bertrand and Cecotti, Hubert and Souloumiac, Antoine and Maby, Emmanuel and Mattout, Jérémie},
year = {2011},
pages = {1382--1386},
file = {[PDF] from inserm.fr:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/AGETBH2R/Rivet et al. - 2011 - Theoretical analysis of xDAWN algorithm applicati.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/HXZZK378/login.html:text/html}
}
@article{herculano-houzel_remarkable_2013,
title = {The {Remarkable}, {Yet} {Not} {Extraordinary}, {Human} {Brain} as a {Scaled}-{Up} {Primate} {Brain} and {Its} {Associated} {Cost}},
url = {http://www.ncbi.nlm.nih.gov/books/NBK207181/},
abstract = {If the basis for cognition lies in the brain, how can it be that the self-designated most cognitively able of animals—us, of course—is not the one endowed with the largest brain? The logic behind the paradox is simple: because brains are made of neurons, it seems reasonable to expect larger brains to be made of larger numbers of neurons; if neurons are the computational units of the brain, then larger brains, made of larger numbers of neurons, should have larger computational abilities than smaller brains. By this logic, humans should not rank even an honorable second in cognitive abilities among animals: at about 1.5 kg, the human brain is two- to threefold smaller than the elephant brain and four- to sixfold smaller than the brains of several cetaceans (Tower, 1954; Marino, 1998). Nevertheless, we are so convinced of our primacy that we carry it explicitly in the name given by Linnaeus to the mammalian order to which we belong—Primata, meaning “first rank,” and we are seemingly the only animal species concerned with developing entire research programs to study itself.},
language = {en},
urldate = {2016-04-14},
author = {Herculano-Houzel, Suzana},
month = jan,
year = {2013},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/S4EVFFVS/NBK207181.html:text/html}
}
@article{gosseries_[functional_2008,
title = {[{Functional} neuroimaging ({fMRI}, {PET} and {MEG}): what do we measure?]},
volume = {63},
issn = {0370-629X},
shorttitle = {[{Functional} neuroimaging ({fMRI}, {PET} and {MEG})},
abstract = {Functional cerebral imaging techniques allow the in vivo study of human cognitive and sensorimotor functions in physiological or pathological conditions. In this paper, we review the advantages and limitations of functional magnetic resonance imaging (fMRI), positron emission tomography (PET) and magnetoencephalography (MEG). fMRI and PET measure haemodynamic changes induced by regional changes in neuronal activity. These techniques have a high spatial resolution (a few millimeters), but a poor temporal resolution (a few seconds to several minutes). Electroencephalogram (EEG) and MEG measure the neuronal electrical or magnetic activity with a high temporal resolution (i.e., milliseconds) albeit with a poorer spatial resolution (i.e., a few millimeters to one centimeter). The combination of these different neuroimaging techniques allows studying different components of the brain's activity (e.g., neurovascular coupling, electromagnetic activity) with both a high temporal and spatial resolution.},
language = {fre},
number = {5-6},
journal = {Revue Médicale De Liège},
author = {Gosseries, O. and Demertzi, A. and Noirhomme, Q. and Tshibanda, J. and Boly, M. and Op de Beeck, M. and Hustinx, R. and Maquet, P. and Salmon, E. and Moonen, G. and Luxen, A. and Laureys, S. and De Tiège, X.},
month = jun,
year = {2008},
pmid = {18669186},
keywords = {Brain, Brain Diseases, Humans, Magnetic resonance imaging, Magnetoencephalography, Positron-Emission Tomography},
pages = {231--237}
}
@article{sajda_brain-computer_2008,
title = {Brain-{Computer} {Interfaces}},
volume = {25},
number = {1},
journal = {Signal Processing Magazine, IEEE},
author = {Sajda, P. and Muller, K. R. and Shenoy, K. V.},
year = {2008},
pages = {16--17}
}
@article{blankertz_single-trial_2011,
title = {Single-trial analysis and classification of {ERP} components: a tutorial},
volume = {56},
number = {2},
journal = {NeuroImage},
author = {Blankertz, Benjamin and Lemm, Steven and Treder, Matthias and Haufe, Stefan and Müller, Klaus-Robert},
year = {2011},
pages = {814--825}
}
@article{hoffmann_efficient_2008,
series = {Brain-{Computer} {Interfaces} ({BCIs})},
title = {An efficient {P}300-based brain–computer interface for disabled subjects},
volume = {167},
issn = {0165-0270},
url = {http://www.sciencedirect.com/science/article/pii/S0165027007001094},
doi = {10.1016/j.jneumeth.2007.03.005},
abstract = {A brain–computer interface (BCI) is a communication system that translates brain-activity into commands for a computer or other devices. In other words, a BCI allows users to act on their environment by using only brain-activity, without using peripheral nerves and muscles. In this paper, we present a BCI that achieves high classification accuracy and high bitrates for both disabled and able-bodied subjects. The system is based on the P300 evoked potential and is tested with five severely disabled and four able-bodied subjects. For four of the disabled subjects classification accuracies of 100\% are obtained. The bitrates obtained for the disabled subjects range between 10 and 25 bits/min. The effect of different electrode configurations and machine learning algorithms on classification accuracy is tested. Further factors that are possibly important for obtaining good classification accuracy in P300-based BCI systems for disabled subjects are discussed.},
number = {1},
urldate = {2016-04-28},
journal = {Journal of Neuroscience Methods},
author = {Hoffmann, Ulrich and Vesin, Jean-Marc and Ebrahimi, Touradj and Diserens, Karin},
month = jan,
year = {2008},
keywords = {Bayesian linear discriminant analysis, Brain–computer interface, Disabled subjects, Fisher's linear discriminant analysis, P300},
pages = {115--125},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/NSNPS5QJ/Hoffmann et al. - 2008 - An efficient P300-based brain–computer interface f.pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/URTMSJZZ/S0165027007001094.html:text/html}
}
@article{leeb_multimodal_2010,
title = {Multimodal {Fusion} of {Muscle} and {Brain} {Signals} for a {Hybrid}-{BCI}},
journal = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE},
author = {Leeb, R. and Sagha, H. and Chavarriaga, R. and del R Millan, J.},
year = {2010},
pages = {4343--4346}
}
@inproceedings{barachant_riemannian_2013,
title = {The {Riemannian} {Potato}: an automatic and adaptive artifact detection method for online experiments using {Riemannian} geometry},
booktitle = {Proceedings of {TOBI} {Workshop} {IV}},
author = {Barachant, Alexandre and Andreev, Anton and Congedo, Marco and {others}},
year = {2013},
pages = {19--20}
}
@article{dornhege_increase_2004,
title = {Increase information transfer rates in {BCI} by {CSP} extension to multi-class},
journal = {Advances in Neural Information Processing Systems},
author = {Dornhege, Guido and Blankertz, Benjamin and Curio, Gabriel and {Klaus-Robert Muller}},
year = {2004},
pages = {733--740}
}
@article{sellers_p300_2006,
title = {A {P}300 event-related potential brain-computer interface ({BCI}): {The} effects of matrix size and inter stimulus interval on performance},
volume = {73},
number = {3},
journal = {Biological Psychology},
author = {Sellers, Eric W. and Krusienski, Dean J. and McFarland, Dennis J. and Vaughan, Theresa M. and Wolpaw, Jonathan R.},
year = {2006},
pages = {242--252}
}
@book{absil_optimization_2009,
title = {Optimization algorithms on matrix manifolds},
publisher = {Princeton University Press},
author = {Absil, P-A and Mahony, Robert and Sepulchre, Rodolphe},
year = {2009}
}
@article{herculano-houzel_human_2009,
title = {The {Human} {Brain} in {Numbers}: {A} {Linearly} {Scaled}-up {Primate} {Brain}},
volume = {3},
issn = {1662-5161},
shorttitle = {The {Human} {Brain} in {Numbers}},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2776484/},
doi = {10.3389/neuro.09.031.2009},
abstract = {The human brain has often been viewed as outstanding among mammalian brains: the most cognitively able, the largest-than-expected from body size, endowed with an overdeveloped cerebral cortex that represents over 80\% of brain mass, and purportedly containing 100 billion neurons and 10× more glial cells. Such uniqueness was seemingly necessary to justify the superior cognitive abilities of humans over larger-brained mammals such as elephants and whales. However, our recent studies using a novel method to determine the cellular composition of the brain of humans and other primates as well as of rodents and insectivores show that, since different cellular scaling rules apply to the brains within these orders, brain size can no longer be considered a proxy for the number of neurons in the brain. These studies also showed that the human brain is not exceptional in its cellular composition, as it was found to contain as many neuronal and non-neuronal cells as would be expected of a primate brain of its size. Additionally, the so-called overdeveloped human cerebral cortex holds only 19\% of all brain neurons, a fraction that is similar to that found in other mammals. In what regards absolute numbers of neurons, however, the human brain does have two advantages compared to other mammalian brains: compared to rodents, and probably to whales and elephants as well, it is built according to the very economical, space-saving scaling rules that apply to other primates; and, among economically built primate brains, it is the largest, hence containing the most neurons. These findings argue in favor of a view of cognitive abilities that is centered on absolute numbers of neurons, rather than on body size or encephalization, and call for a re-examination of several concepts related to the exceptionality of the human brain.},
urldate = {2016-04-14},
journal = {Frontiers in Human Neuroscience},
author = {Herculano-Houzel, Suzana},
month = nov,
year = {2009},
pmid = {19915731},
pmcid = {PMC2776484},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/X33G6FH7/Herculano-Houzel - 2009 - The Human Brain in Numbers A Linearly Scaled-up P.pdf:application/pdf}
}
@article{miltner_event-related_1997,
title = {Event-{Related} {Brain} {Potentials} {Following} {Incorrect} {Feedback} in a {Time}-{Estimation} {Task}: {Evidence} for a “{Generic}” {Neural} {System} for {Error} {Detection}},
volume = {9},
issn = {0898-929X},
shorttitle = {Event-{Related} {Brain} {Potentials} {Following} {Incorrect} {Feedback} in a {Time}-{Estimation} {Task}},
url = {http://dx.doi.org/10.1162/jocn.1997.9.6.788},
doi = {10.1162/jocn.1997.9.6.788},
abstract = {We examined scalp-recorded event-related potentials following feedback stimuli in a time-estimation task. Six hundred msec after indicating the end of a 1 sec interval, subjects received a visual, auditory, or somatosensory stimulus that indicated whether the interval they had produced was correct. Following feedback indicating incorrect performance, a negative deflection occurred, whose characteristics corresponded closely to those of the component (the error-related negativity) that accompanies errors in choice reaction time tasks. Furthermore, equivalent dipole analysis suggested that, for all three modalities, the distribution of the scalp potential was consistent with a local source in the anterior cingulate cortex or a more distributed source in the supplementary motor areas. These loci correspond closely to those described previously for the error-related negativity. We conclude that the error-related negativity is the manifestation of the activity of a “generic” neural system involved in error detection.},
number = {6},
urldate = {2016-04-26},
journal = {Journal of Cognitive Neuroscience},
author = {Miltner, Wolfgang H. R. and Braun, Christoph H. and Coles, Michael G. H.},
month = nov,
year = {1997},
pages = {788--798},
file = {Journal of Cognitive Neuroscience Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/DENI4RN8/jocn.1997.9.6.html:text/html}
}
@inproceedings{kottaimalai_eeg_2013,
title = {{EEG} signal classification using principal component analysis with neural network in brain computer interface applications},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6528498},
urldate = {2016-05-11},
booktitle = {Emerging {Trends} in {Computing}, {Communication} and {Nanotechnology} ({ICE}-{CCN}), 2013 {International} {Conference} on},
publisher = {IEEE},
author = {Kottaimalai, R. and Rajasekaran, M. Pallikonda and Selvam, V. and Kannapiran, B.},
year = {2013},
pages = {227--231},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/PE2PT38J/login.html:text/html}
}
@article{sturm_interpretable_2016,
title = {Interpretable {Deep} {Neural} {Networks} for {Single}-{Trial} {EEG} {Classification}},
url = {http://arxiv.org/abs/1604.08201},
urldate = {2016-05-12},
journal = {arXiv preprint arXiv:1604.08201},
author = {Sturm, Irene and Bach, Sebastian and Samek, Wojciech and Müller, Klaus-Robert},
year = {2016},
file = {[PDF] from arxiv.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BTVMPKBR/Sturm et al. - 2016 - Interpretable Deep Neural Networks for Single-Tria.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QKBXXD5H/1604.html:text/html}
}
@article{ang_clinical_2010,
title = {Clinical study of neurorehabilitation in stroke using {EEG}-based motor imagery brain-computer interface with robotic feedback},
journal = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE},
author = {Ang, Kai Keng and Guan, Cuntai and Chua, K.S.G. and Ang, Beng Ti and Kuah, C. and Wang, Chuanchu and Phua, Kok Soon and Chin, Zheng Yang and Zhang, Haihong},
year = {2010},
pages = {5549--5552}
}
@article{eimer_effects_2000,
title = {Effects of face inversion on the structural encoding and recognition of faces: {Evidence} from event-related brain potentials},
volume = {10},
shorttitle = {Effects of face inversion on the structural encoding and recognition of faces},
url = {http://www.sciencedirect.com/science/article/pii/S0926641000000380},
number = {1},
urldate = {2016-02-01},
journal = {Cognitive Brain Research},
author = {Eimer, Martin},
year = {2000},
pages = {145--158},
file = {[PDF] from bbk.ac.uk:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/IHDTRS8W/Eimer - 2000 - Effects of face inversion on the structural encodi.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/7FEFW7KJ/S0926641000000380.html:text/html}
}
@article{schoot_penfields_1993,
title = {Penfield's homunculus: a note on cerebral cartography},
volume = {56},
number = {4},
journal = {Journal of Neurology, Neurosurgery, and Psychiatry},
author = {Schoot, G.D.},
year = {1993},
pages = {329--333}
}
@article{engemann_automated_2015,
title = {Automated model selection in covariance estimation and spatial whitening of {MEG} and {EEG} signals},
volume = {108},
url = {http://www.sciencedirect.com/science/article/pii/S1053811914010325},
urldate = {2016-03-14},
journal = {NeuroImage},
author = {Engemann, Denis A. and Gramfort, Alexandre},
year = {2015},
pages = {328--342},
file = {[PDF] à partir de psu.edu:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QMNRQFGB/Engemann and Gramfort - 2015 - Automated model selection in covariance estimation.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BUP9ZJ5I/S1053811914010325.html:text/html}
}
@article{hochberg_neuronal_2006,
title = {Neuronal ensemble control of prosthetic devices by a human with tetraplegia},
volume = {442},
copyright = {© 2006 Nature Publishing Group},
issn = {0028-0836},
url = {http://www.nature.com/nature/journal/v442/n7099/abs/nature04970.html},
doi = {10.1038/nature04970},
abstract = {Neuromotor prostheses (NMPs) aim to replace or restore lost motor functions in paralysed humans by routeing movement-related signals from the brain, around damaged parts of the nervous system, to external effectors. To translate preclinical results from intact animals to a clinically useful NMP, movement signals must persist in cortex after spinal cord injury and be engaged by movement intent when sensory inputs and limb movement are long absent. Furthermore, NMPs would require that intention-driven neuronal activity be converted into a control signal that enables useful tasks. Here we show initial results for a tetraplegic human (MN) using a pilot NMP. Neuronal ensemble activity recorded through a 96-microelectrode array implanted in primary motor cortex demonstrated that intended hand motion modulates cortical spiking patterns three years after spinal cord injury. Decoders were created, providing a 'neural cursor' with which MN opened simulated e-mail and operated devices such as a television, even while conversing. Furthermore, MN used neural control to open and close a prosthetic hand, and perform rudimentary actions with a multi-jointed robotic arm. These early results suggest that NMPs based upon intracortical neuronal ensemble spiking activity could provide a valuable new neurotechnology to restore independence for humans with paralysis.},
language = {en},
number = {7099},
urldate = {2016-04-18},
journal = {Nature},
author = {Hochberg, Leigh R. and Serruya, Mijail D. and Friehs, Gerhard M. and Mukand, Jon A. and Saleh, Maryam and Caplan, Abraham H. and Branner, Almut and Chen, David and Penn, Richard D. and Donoghue, John P.},
month = jul,
year = {2006},
pages = {164--171},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/THX6VJW7/Hochberg et al. - 2006 - Neuronal ensemble control of prosthetic devices by.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/J9Z92GVP/nature04970.html:text/html}
}
@inproceedings{li_analysis_2011,
title = {Analysis of phase coding {SSVEP} based on canonical correlation analysis ({CCA})},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5910563},
urldate = {2016-05-22},
booktitle = {Neural {Engineering} ({NER}), 2011 5th {International} {IEEE}/{EMBS} {Conference} on},
publisher = {IEEE},
author = {Li, Yun and Bin, Guangyu and Gao, Xiaorong and Hong, Bo and Gao, Shangkai},
year = {2011},
pages = {368--371},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/WBBJSDHF/login.html:text/html}
}
@article{muller_feature-selective_2006-1,
title = {Feature-selective attention enhances color signals in early visual areas of the human brain},
volume = {103},
issn = {0027-8424},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1599943/},
doi = {10.1073/pnas.0606668103},
abstract = {We used an electrophysiological measure of selective stimulus processing (the steady-state visual evoked potential, SSVEP) to investigate feature-specific attention to color cues. Subjects viewed a display consisting of spatially intermingled red and blue dots that continually shifted their positions at random. The red and blue dots flickered at different frequencies and thereby elicited distinguishable SSVEP signals in the visual cortex. Paying attention selectively to either the red or blue dot population produced an enhanced amplitude of its frequency-tagged SSVEP, which was localized by source modeling to early levels of the visual cortex. A control experiment showed that this selection was based on color rather than flicker frequency cues. This signal amplification of attended color items provides an empirical basis for the rapid identification of feature conjunctions during visual search, as proposed by “guided search” models.},
number = {38},
urldate = {2016-05-02},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
author = {Müller, M. M. and Andersen, S. and Trujillo, N. J. and Valdés-Sosa, P. and Malinowski, P. and Hillyard, S. A.},
month = sep,
year = {2006},
pmid = {16956975},
pmcid = {PMC1599943},
pages = {14250--14254},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/TEN958TH/Müller et al. - 2006 - Feature-selective attention enhances color signals.pdf:application/pdf}
}
@article{ang_filter_2008,
title = {Filter {Bank} {Common} {Spatial} {Pattern} ({FBCSP}) in {Brain}-{Computer} {Interface}},
journal = {Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on},
author = {Ang, Kai Keng and Chin, Zhang Yang and Zhang, Haihong and Guan, Cuntai},
year = {2008},
pages = {2390--2397}
}
@article{friedman_regularized_1989,
title = {Regularized {Discriminant} {Analysis}},
volume = {84},
number = {405},
journal = {Journal of the American Statistical Association},
author = {Friedman, Jerome H.},
year = {1989},
pages = {165--175}
}
@article{mueller-putz_better_2008,
title = {Better than random: {A} closer look on {BCI} results.},
volume = {10},
number = {1},
journal = {International Journal of Bioelectromagnetism},
author = {Mueller-Putz, Gernot and Scherer, Reinhold and Brunner, Clemens and Leeb, Robert and Pfurtscheller, Gert},
year = {2008},
pages = {52--55}
}
@article{lim_matrix_2012,
title = {Matrix power means and the {Karcher} mean},
volume = {262},
url = {http://www.sciencedirect.com/science/article/pii/S0022123611004101},
number = {4},
urldate = {2016-06-23},
journal = {Journal of Functional Analysis},
author = {Lim, Yongdo and Pálfia, Miklós},
year = {2012},
pages = {1498--1514},
file = {[HTML] from sciencedirect.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/P3IWJ5CW/S0022123611004101.html:text/html}
}
@article{krusienski_toward_2008,
title = {Toward {Enhanced} {P}300 {Speller} {Performance}},
volume = {167},
number = {1},
journal = {Journal of Neuroscience Methods},
author = {Krusienski, Dean J. and Sellers, Eric W. and McFarland, Dennis J. and Vaughan, Theresa M. and Wolpaw, Jonathan R.},
year = {2008},
pages = {15--21}
}
@book{lee_introduction_2010,
title = {Introduction to topological manifolds},
volume = {940},
publisher = {Springer},
author = {Lee, John},
year = {2010}
}
@article{elshout_review_2009,
title = {Review of brain-computer interfaces based on the {P}300 evoked potential},
url = {http://dspace.library.uu.nl/handle/1874/33417},
urldate = {2016-05-02},
author = {Elshout, J. A.},
year = {2009},
file = {[PDF] from uu.nl:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/T447U4GI/Elshout - 2009 - Review of brain-computer interfaces based on the P.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/J6UNPWGD/33417.html:text/html}
}
@inproceedings{geras_multiple-source_2013,
title = {Multiple-source cross-validation},
url = {http://jmlr.org/proceedings/papers/v28/geras13.html},
urldate = {2016-02-10},
author = {Geras, Krzysztof and Sutton, Charles},
year = {2013},
pages = {1292--1300},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/VBANVQHX/Geras and Sutton - 2013 - Multiple-source cross-validation.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/Q4FFUEMH/geras13.html:text/html}
}
@article{cecotti_time-frequency_2011,
title = {A time-frequency convolutional neural network for the offline classification of steady-state visual evoked potential responses},
volume = {32},
number = {8},
journal = {Pattern Recognition Letters},
author = {Cecotti, Hubert},
year = {2011},
pages = {1145 -- 1153}
}
@inproceedings{aloise_asynchronous_????,
title = {Asynchronous control in a {P}300 task for domotic control},
url = {http://www.tobi-project.org/sites/default/files/public/Publications/AloiseEtAll_BCI2010.pdf},
urldate = {2016-04-28},
booktitle = {4th {International} {BCI} {Meeting}, {Asilomar}, {California} {May}},
author = {Aloise, F. and Schettini, F. and Quitadamo, L. and Bianchi, L. and Babiloni, F. and Mattia, D. and Cincotti, F.},
file = {[PDF] from tobi-project.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/EN5A9GFI/Aloise et al. - Asynchronous control in a P300 task for domotic co.pdf:application/pdf}
}
@book{purves_neuroscience_2008-1,
edition = {4th edition},
title = {Neuroscience, {Fourth} {Edition}},
isbn = {978-0-87893-697-7},
abstract = {Neuroscience is a comprehensive textbook created primarily for medical, premedical, and undergraduate students. In a single concise and approachable volume, the text guides students through the challenges and excitement of this rapidly changing field. The book s length and accessibility of its writing are a successful combination that has proven to work equally well for medical students and in undergraduate neuroscience courses. Being both comprehensive and authoritative, the book is also appropriate for graduate and professional use.},
language = {English},
publisher = {Sinauer Associates, Inc.},
author = {Purves, Dale},
month = jul,
year = {2008}
}
@book{sornmo_bioelectrical_2005,
title = {Bioelectrical {Signal} {Processing} in {Cardiac} and {Neurological} {Applications}},
isbn = {978-0-12-437552-9},
publisher = {Elsevier Academic Press},
author = {Sörnmo, Leif and Laguna, Pablo},
year = {2005}
}
@article{maratos_when_2015,
title = {When is a face a face? {Schematic} faces, emotion, attention and the {N}170},
volume = {2},
shorttitle = {When is a face a face?},
url = {http://eprints.soton.ac.uk/383991/},
number = {3},
urldate = {2016-02-01},
journal = {AIMS Neuroscience},
author = {Maratos, Frances A. and Garner, Matthew and Hogan, Alexandra M. and Karl, Anke},
year = {2015},
pages = {172--182},
file = {[PDF] from soton.ac.uk:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BJQSKKSP/Maratos et al. - 2015 - When is a face a face Schematic faces, emotion, a.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/R35D3NIH/383991.html:text/html}
}
@article{toro_c._and_deuschl_g_and_thatcher_r_and_sato_s._and_kufta_c_and_hallett_m._event-related_1994,
title = {Event-related desynchronization and movement-related cortical potentials on the {ECoG} and {EEG}},
volume = {93},
number = {5},
journal = {Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section},
author = {{Toro, C. and Deuschl, G and Thatcher, R and Sato, S. and Kufta, C and Hallett, M.}},
year = {1994},
pages = {380--389}
}
@article{hjorth_-line_1975,
title = {An on-line transformation of {EEG} scalp potentials into orthogonal source derivations},
volume = {39},
number = {5},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Hjorth, Bo},
year = {1975},
pages = {526--530}
}
@article{ledoit_well-conditioned_2004,
title = {A well-conditioned estimator for large-dimensional covariance matrices},
volume = {88},
number = {2},
journal = {Journal of multivariate analysis},
author = {Ledoit, Olivier and Wolf, Michael},
year = {2004},
pages = {365--411}
}
@article{belkin_laplacian_2003,
title = {Laplacian {Eigenmaps} for {Dimensionality} {Reduction} and {Data} {Representation}},
volume = {15},
url = {http://neco.mitpress.org/cgi/content/abstract/15/6/1373},
abstract = {One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a representation for data lying on a low-dimensional manifold embedded in a high-dimensional space. Drawing on the correspondence between the graph Laplacian, the Laplace Beltrami operator on the manifold, and the connections to the heat equation, we propose a geometrically motivated algorithm for representing the high-dimensional data. The algorithm provides a computationally efficient approach to nonlinear dimensionality reduction that has locality-preserving properties and a natural connection to clustering. Some potential applications and illustrative examples are discussed.},
number = {6},
urldate = {2015-05-13},
journal = {Neural Comp.},
author = {Belkin, Mikhail and Niyogi, Partha},
month = jun,
year = {2003},
keywords = {dimension\_reduction, laplacian\_eigenmap, nonlinear, projection},
pages = {1373--1396}
}
@article{li_electroencephalogram_2012,
title = {Electroencephalogram signals classification for sleepstate decision: {A} {Riemannian} geometry approach},
volume = {6},
number = {4},
journal = {Signal Processing, IET},
author = {Li, Y and Wong, KM and De Bruin, H},
year = {2012},
pages = {288--299}
}
@misc{_modification_????,
title = {Modification of {N}170 by different emotional expression of schematic faces},
url = {https://www-sciencedirect-com.etna.bib.uvsq.fr/science/article/pii/S0301051107001184},
urldate = {2016-02-01},
file = {Modification of N170 by different emotional expression of schematic faces:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/U5CVMAZM/S0301051107001184.html:text/html}
}
@article{oralhan_effect_2016,
title = {The {Effect} of {Duty} {Cycle} and {Brightness} {Variation} of {Visual} {Stimuli} on {SSVEP} in {Brain} {Computer} {Interface} {Systems}},
url = {http://www.tandfonline.com/doi/abs/10.1080/03772063.2016.1176543},
urldate = {2016-05-12},
journal = {IETE Journal of Research},
author = {Oralhan, Zeki and Tokmakçi, Mahmut},
year = {2016},
pages = {1--9},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/HJK26PSG/03772063.2016.html:text/html}
}
@article{yoo_braincomputer_2004,
title = {Brain–computer interface using {fMRI}: spatial navigation by thoughts},
volume = {15},
shorttitle = {Brain–computer interface using {fMRI}},
url = {http://journals.lww.com/neuroreport/Abstract/2004/07190/Brain_computer_interface_using_fMRI__spatial.12.aspx},
number = {10},
urldate = {2016-04-19},
journal = {Neuroreport},
author = {Yoo, Seung-Schik and Fairneny, Ty and Chen, Nan-Kuei and Choo, Seh-Eun and Panych, Lawrence P. and Park, HyunWook and Lee, Soo-Young and Jolesz, Ferenc A.},
year = {2004},
pages = {1591--1595},
file = {[PDF] from ismrm.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/83W55UCR/Yoo et al. - 2004 - Brain–computer interface using fMRI spatial navig.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ZVMFCW97/Brain_computer_interface_using_fMRI__spatial.12.html:text/html}
}
@article{raudys_small_1991,
title = {Small sample size effects in statistical pattern recognition: recommendations for practitioners},
shorttitle = {Small sample size effects in statistical pattern recognition},
url = {http://www.computer.org/csdl/trans/tp/1991/03/i0252.pdf},
number = {3},
urldate = {2016-05-29},
journal = {IEEE Transactions on Pattern Analysis \& Machine Intelligence},
author = {Raudys, Sarunas J. and Jain, Anil K.},
year = {1991},
pages = {252--264},
file = {[PDF] from msu.edu:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/XIZVC8KQ/Raudys and Jain - 1991 - Small sample size effects in statistical pattern r.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/UZRPGMQU/i0252.html:text/html}
}
@article{ciresan_high-performance_2011,
title = {High-performance neural networks for visual object classification},
journal = {arXiv preprint arXiv:1102.0183},
author = {Cireşan, Dan C and Meier, Ueli and Masci, Jonathan and Gambardella, Luca M and Schmidhuber, Jürgen},
year = {2011}
}
@article{bregman_relaxation_1967,
title = {The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming},
volume = {7},
url = {http://www.sciencedirect.com/science/article/pii/0041555367900407},
number = {3},
urldate = {2016-06-23},
journal = {USSR computational mathematics and mathematical physics},
author = {Bregman, Lev M.},
year = {1967},
pages = {200--217},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/D486URAV/0041555367900407.html:text/html}
}
@article{nielsen_clustering_2014,
title = {On clustering histograms with k-means by using mixed $\alpha$-divergences},
volume = {16},
url = {http://www.mdpi.com/1099-4300/16/6/3273/htm},
number = {6},
urldate = {2016-06-23},
journal = {Entropy},
author = {Nielsen, Frank and Nock, Richard and Amari, Shun-ichi},
year = {2014},
pages = {3273--3301},
file = {[HTML] from mdpi.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BXK9ASNN/htm.html:text/html}
}
@article{wolpaw_brain-computer_2000,
title = {Brain-computer interface technology: a review of the first international meeting},
volume = {8},
number = {2},
journal = {Rehabilitation Engineering, IEEE Transactions on},
author = {Wolpaw, Jonathan R. and Birbaumer, N. and Heetderks, W.J. and McFarland, Dennis J. and Peckham, P.H. and Schalk, G. and Donchin, E. and Quatrano, L.A. and Robinson, C.J. and Vaughan, T.M.},
year = {2000},
pages = {164--173}
}
@article{lotte_review_2007,
title = {A review of classification algorithms for {EEG}-based brain-computer interfaces.},
volume = {4},
number = {2},
journal = {Journal of Neural Engineering},
author = {Lotte, F. and Congedo, M. and Lécuyer, A. and Lamarche, F. and Arnaldi, B.},
year = {2007},
pages = {R1}
}
@article{tiganj_online_2012,
title = {Online frequency band estimation and change-point detection},
journal = {Systems and Computer Science (ICSCS), 2012 1st International Conference on},
author = {Tiganj, Zoran and Mboup, Mamadou and Chevallier, Sylvain and Kalunga, Emmanuel},
year = {2012},
pages = {1--6}
}
@article{hoang_experiments_2011,
title = {Experiments on using combined short window bivariate autoregression for {EEG} classification},
journal = {Neural Engineering (NER), 2011 5th International IEEE/EMBS Conference on},
author = {Hoang, Tuan and Tran, Dat and Nguyen, Phuoc and Huang, Xu and Sharma, D.},
year = {2011},
pages = {372--375}
}
@article{sra_positive_2016,
title = {Positive definite matrices and the {S}-divergence},
volume = {144},
issn = {0002-9939, 1088-6826},
url = {http://www.ams.org/proc/2016-144-07/S0002-9939-2015-12953-X/},
doi = {10.1090/proc/12953},
abstract = {Hermitian positive definite (hpd) matrices form a self-dual convex cone whose interior is a Riemannian manifold of nonpositive curvature. The manifold view comes with a natural distance function but the conic view does not. Thus, drawing motivation from convex optimization we introduce the S-divergence, a distance-like function on the cone of hpd matrices. We study basic properties of the S-divergence and explore its connections to the Riemannian distance. In particular, we show that (i) its square-root is a distance, and (ii) it exhibits numerous nonpositive-curvature-like properties.},
number = {7},
urldate = {2016-06-23},
journal = {Proceedings of the American Mathematical Society},
author = {Sra, Suvrit},
year = {2016},
pages = {2787--2797},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/PMDJ7UFK/S0002-9939-2015-12953-X.html:text/html}
}
@article{tu_subject_2012,
title = {A subject transfer framework for {EEG} classification},
volume = {82},
journal = {Neurocomputing},
author = {Tu, Wenting and Sun, Shiliang},
year = {2012},
pages = {109--116}
}
@inproceedings{goh_unsupervised_2008,
title = {Unsupervised {Riemannian} clustering of probability density functions},
booktitle = {Machine {Learning} and {Knowledge} {Discovery} in {Databases}},
publisher = {Springer},
author = {Goh, Alvina and Vidal, René},
year = {2008},
pages = {377--392}
}
@article{wang_electrocorticographic_2013,
title = {An {Electrocorticographic} {Brain} {Interface} in an {Individual} with {Tetraplegia}},
volume = {8},
issn = {1932-6203},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3566209/},
doi = {10.1371/journal.pone.0055344},
abstract = {Brain-computer interface (BCI) technology aims to help individuals with disability to control assistive devices and reanimate paralyzed limbs. Our study investigated the feasibility of an electrocorticography (ECoG)-based BCI system in an individual with tetraplegia caused by C4 level spinal cord injury. ECoG signals were recorded with a high-density 32-electrode grid over the hand and arm area of the left sensorimotor cortex. The participant was able to voluntarily activate his sensorimotor cortex using attempted movements, with distinct cortical activity patterns for different segments of the upper limb. Using only brain activity, the participant achieved robust control of 3D cursor movement. The ECoG grid was explanted 28 days post-implantation with no adverse effect. This study demonstrates that ECoG signals recorded from the sensorimotor cortex can be used for real-time device control in paralyzed individuals.},
number = {2},
urldate = {2016-04-15},
journal = {PLoS ONE},
author = {Wang, Wei and Collinger, Jennifer L. and Degenhart, Alan D. and Tyler-Kabara, Elizabeth C. and Schwartz, Andrew B. and Moran, Daniel W. and Weber, Douglas J. and Wodlinger, Brian and Vinjamuri, Ramana K. and Ashmore, Robin C. and Kelly, John W. and Boninger, Michael L.},
month = feb,
year = {2013},
pmid = {23405137},
pmcid = {PMC3566209},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/Z7UAG4RZ/Wang et al. - 2013 - An Electrocorticographic Brain Interface in an Ind.pdf:application/pdf}
}
@article{lalor_steady-state_2005,
title = {Steady-state {VEP}-based brain-computer interface control in an immersive 3D gaming environment},
volume = {2005},
journal = {EURASIP Journal on Applied Signal Processing},
author = {Lalor, E. C. and Kelly, S. P. and Finucane, C. and Burke, R. and Smith, R. and Reilly, R. B. and McDarby, G.},
year = {2005},
pages = {3156--3164}
}
@article{haselsteiner_using_2000,
title = {Using time-dependent neural networks for {EEG} classification},
volume = {8},
number = {4},
journal = {Rehabilitation Engineering, IEEE Transactions on},
author = {Haselsteiner, E. and Pfurtscheller, G.},
year = {2000},
pages = {457--463}
}
@article{donchin_discriminant_1969,
title = {Discriminant analysis in average evoked response studies: the study of single trial data},
volume = {27},
shorttitle = {Discriminant analysis in average evoked response studies},
url = {http://www.sciencedirect.com/science/article/pii/0013469469900613},
number = {3},
urldate = {2016-04-12},
journal = {Electroencephalography and clinical neurophysiology},
author = {Donchin, Emanuel},
year = {1969},
pages = {311--314},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/GSHPPA6T/0013469469900613.html:text/html}
}
@article{pfurtscheller_event-related_1992,
title = {Event-related synchronization ({ERS}): an electrophysiological correlate of cortical areas at rest},
volume = {83},
number = {1},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {{Pfurtscheller}},
year = {1992},
pages = {62--69}
}
@article{golub_motor_2014,
title = {Motor cortical control of movement speed with implications for brain-machine interface control},
volume = {112},
copyright = {Copyright © 2014 the American Physiological Society},
issn = {0022-3077, 1522-1598},
url = {http://jn.physiology.org/content/112/2/411},
doi = {10.1152/jn.00391.2013},
abstract = {Motor cortex plays a substantial role in driving movement, yet the details underlying this control remain unresolved. We analyzed the extent to which movement-related information could be extracted from single-trial motor cortical activity recorded while monkeys performed center-out reaching. Using information theoretic techniques, we found that single units carry relatively little speed-related information compared with direction-related information. This result is not mitigated at the population level: simultaneously recorded population activity predicted speed with significantly lower accuracy relative to direction predictions. Furthermore, a unit-dropping analysis revealed that speed accuracy would likely remain lower than direction accuracy, even given larger populations. These results suggest that the instantaneous details of single-trial movement speed are difficult to extract using commonly assumed coding schemes. This apparent paucity of speed information takes particular importance in the context of brain-machine interfaces (BMIs), which rely on extracting kinematic information from motor cortex. Previous studies have highlighted subjects' difficulties in holding a BMI cursor stable at targets. These studies, along with our finding of relatively little speed information in motor cortex, inspired a speed-dampening Kalman filter (SDKF) that automatically slows the cursor upon detecting changes in decoded movement direction. Effectively, SDKF enhances speed control by using prevalent directional signals, rather than requiring speed to be directly decoded from neural activity. SDKF improved success rates by a factor of 1.7 relative to a standard Kalman filter in a closed-loop BMI task requiring stable stops at targets. BMI systems enabling stable stops will be more effective and user-friendly when translated into clinical applications.},
language = {en},
number = {2},
urldate = {2016-04-18},
journal = {Journal of Neurophysiology},
author = {Golub, Matthew D. and Yu, Byron M. and Schwartz, Andrew B. and Chase, Steven M.},
month = jul,
year = {2014},
pmid = {24717350},
pages = {411--429},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/9CWAU3MR/Golub et al. - 2014 - Motor cortical control of movement speed with impl.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/SI8C5EFJ/411.html:text/html}
}
@article{bedard_model_2006,
title = {Model of low-pass filtering of local field potentials in brain tissue},
volume = {73},
journal = {Nonlinear Soft Matter Physics},
author = {Bédard, C. and Kröger, H. and Destexhe, A.},
year = {2006},
pages = {051911}
}
@article{huang_empirical_1998,
title = {The empirical mode decomposition and the {Hilbert} spectrum for nonlinear and non-stationary time series analysis},
volume = {454},
journal = {Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences},
author = {Huang, N. E. and Shen, Z. and Long, S. R. and Wu, M. C. and Shih, H. H. and Zheng, Q. and Yen, N. C. and Tung, C. C. and Liu, H. H.},
year = {1998},
pages = {903--995}
}
@article{pierce_n250_2011,
title = {The {N}250 {Brain} {Potential} to {Personally} {Familiar} and {Newly} {Learned} {Faces} and {Objects}},
volume = {5},
issn = {1662-5161},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3204460/},
doi = {10.3389/fnhum.2011.00111},
abstract = {Studies employing event-related potentials have shown that when participants are monitoring for a novel target face, the presentation of their own face elicits an enhanced negative brain potential in posterior channels approximately 250 ms after stimulus onset. Here, we investigate whether the own face N250 effect generalizes to other highly familiar objects, specifically, images of the participant’s own dog and own car. In our experiments, participants were asked to monitor for a pre-experimentally unfamiliar target face (Joe), a target dog (Experiment 1: Joe’s Dog) or a target car (Experiment 2: Joe’s Car). The target face and object stimuli were presented with non-target foils that included novel face and object stimuli, the participant’s own face, their own dog (Experiment 1), and their own car (Experiment 2). The consistent findings across the two experiments were the following: (1) the N250 potential differentiated the target faces and objects from the non-target face and object foils and (2) despite being non-targets, the own face and own objects produced an N250 response that was equal in magnitude to the target faces and objects by the end of the experiment. Thus, as indicated by its response to personally familiar and recently familiarized faces and objects, the N250 component is a sensitive index of individuated representations in visual memory.},
urldate = {2016-04-26},
journal = {Frontiers in Human Neuroscience},
author = {Pierce, Lara J. and Scott, Lisa S. and Boddington, Sophie and Droucker, Danielle and Curran, Tim and Tanaka, James W.},
month = oct,
year = {2011},
pmid = {22059071},
pmcid = {PMC3204460},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/5F6UHBQH/Pierce et al. - 2011 - The N250 Brain Potential to Personally Familiar an.pdf:application/pdf}
}
@article{kaufmann_comparison_2013,
title = {Comparison of tactile, auditory, and visual modality for brain-computer interface use: a case study with a patient in the locked-in state},
volume = {7},
issn = {1662-4548},
shorttitle = {Comparison of tactile, auditory, and visual modality for brain-computer interface use},
doi = {10.3389/fnins.2013.00129},
abstract = {This paper describes a case study with a patient in the classic locked-in state, who currently has no means of independent communication. Following a user-centered approach, we investigated event-related potentials (ERP) elicited in different modalities for use in brain-computer interface (BCI) systems. Such systems could provide her with an alternative communication channel. To investigate the most viable modality for achieving BCI based communication, classic oddball paradigms (1 rare and 1 frequent stimulus, ratio 1:5) in the visual, auditory and tactile modality were conducted (2 runs per modality). Classifiers were built on one run and tested offline on another run (and vice versa). In these paradigms, the tactile modality was clearly superior to other modalities, displaying high offline accuracy even when classification was performed on single trials only. Consequently, we tested the tactile paradigm online and the patient successfully selected targets without any error. Furthermore, we investigated use of the visual or tactile modality for different BCI systems with more than two selection options. In the visual modality, several BCI paradigms were tested offline. Neither matrix-based nor so-called gaze-independent paradigms constituted a means of control. These results may thus question the gaze-independence of current gaze-independent approaches to BCI. A tactile four-choice BCI resulted in high offline classification accuracies. Yet, online use raised various issues. Although performance was clearly above chance, practical daily life use appeared unlikely when compared to other communication approaches (e.g., partner scanning). Our results emphasize the need for user-centered design in BCI development including identification of the best stimulus modality for a particular user. Finally, the paper discusses feasibility of EEG-based BCI systems for patients in classic locked-in state and compares BCI to other AT solutions that we also tested during the study.},
language = {eng},
journal = {Frontiers in Neuroscience},
author = {Kaufmann, Tobias and Holz, Elisa M. and Kübler, Andrea},
year = {2013},
pmid = {23898236},
pmcid = {PMC3721006},
keywords = {assistive technology, brain-computer interface, end-user testing, locked-in syndrome, tactile auditory and visual modality, user-centered design},
pages = {129}
}
@article{pfurtscheller_event-related_1999,
title = {Event-related {EEG}/{MEG} synchronization and desynchronization: basic principles.},
volume = {110},
number = {11},
journal = {Clinical Neurophysiology},
author = {Pfurtscheller, G. and Lopes da Silva, F. H.},
year = {1999},
pages = {1842--1857}
}
@article{nakanishi_high-speed_2014,
title = {A high-speed brain speller using steady-state visual evoked potentials},
volume = {24},
url = {http://www.worldscientific.com/doi/abs/10.1142/S0129065714500191},
number = {06},
urldate = {2016-05-02},
journal = {International journal of neural systems},
author = {Nakanishi, Masaki and Wang, Yijun and Wang, Yu-Te and Mitsukura, Yasue and Jung, Tzyy-Ping},
year = {2014},
pages = {1450019},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/AM9R5FHH/Nakanishi et al. - 2014 - A high-speed brain speller using steady-state visu.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/WVRFZ9DX/S0129065714500191.html:text/html}
}
@article{chen_survey_2015,
title = {A survey of the dummy face and human face stimuli used in {BCI} paradigm},
volume = {239},
issn = {0165-0270},
url = {http://www.sciencedirect.com/science/article/pii/S0165027014003628},
doi = {10.1016/j.jneumeth.2014.10.002},
abstract = {Background
It was proved that the human face stimulus were superior to the flash only stimulus in BCI system. However, human face stimulus may lead to copyright infringement problems and was hard to be edited according to the requirement of the BCI study. Recently, it was reported that facial expression changes could be done by changing a curve in a dummy face which could obtain good performance when it was applied to visual-based P300 BCI systems.
New method
In this paper, four different paradigms were presented, which were called dummy face pattern, human face pattern, inverted dummy face pattern and inverted human face pattern, to evaluate the performance of the dummy faces stimuli compared with the human faces stimuli.
Comparison with existing method(s)
The key point that determined the value of dummy faces in BCI systems were whether dummy faces stimuli could obtain as good performance as human faces stimuli. Online and offline results of four different paradigms would have been obtained and comparatively analyzed.
Results
Online and offline results showed that there was no significant difference among dummy faces and human faces in ERPs, classification accuracy and information transfer rate when they were applied in BCI systems.
Conclusions
Dummy faces stimuli could evoke large ERPs and obtain as high classification accuracy and information transfer rate as the human faces stimuli. Since dummy faces were easy to be edited and had no copyright infringement problems, it would be a good choice for optimizing the stimuli of BCI systems.},
urldate = {2016-04-28},
journal = {Journal of Neuroscience Methods},
author = {Chen, Long and Jin, Jing and Zhang, Yu and Wang, Xingyu and Cichocki, Andrzej},
month = jan,
year = {2015},
keywords = {Brain-computer interface (BCI), Dummy face, event-related potentials, Human face},
pages = {18--27},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/4PPCN2PM/Chen et al. - 2015 - A survey of the dummy face and human face stimuli .pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/7UPTUHEZ/S0165027014003628.html:text/html}
}
@article{hammer_psychological_2012,
title = {Psychological predictors of {SMR}-{BCI} performance},
volume = {89},
abstract = {After about 30 years of research on Brain-Computer Interfaces (BCIs) there is little knowledge about the phenomenon, that some people - healthy as well as individuals with disease – are not able to learn BCI-control. To elucidate this " BCI-inefficiency" phenomenon, the current study investigated whether psychological parameters, such as attention span, personality or motivation, could predict performance in a single session with a BCI controlled by modulation of sensorimotor rhythms (SMR) with motor imagery. A total of N = 83 healthy BCI novices took part in the session. Psychological parameters were measured with an electronic test-battery including clinical, personality and performance tests. Predictors were determined by binary logistic regression analyses. The output variable of the Two-Hand Coordination Test (2HAND) {\textbackslash}" overall mean error duration{\textbackslash}" which is a measure for the accuracy of fine motor skills accounted for 11\% of the variance in BCI-inefficiency. The Attitudes Towards Work (AHA) test variable {\textbackslash}"performance level{\textbackslash}" which can be interpreted as a degree of concentration and a neurophysiological SMR predictor were also identified as significant predictors of SMR BCI performance. Psychological parameters as measured in this study play a moderate role for one-session performance in a BCI controlled by modulation of SMR. Fine motor skills predict SMR-BCI performance. The amount of concentration predicts SMR-BCI performance. Biological, psychological and physiological factors lead to an explanation of 30\% of the variance in SMR-BCI performance.},
number = {1},
journal = {Biological Psychology},
author = {Hammer, Eva M. and Halder, Sebastian and Blankertz, Benjamin and Sannelli, Claudia and Dickhaus, Thorsten and Kleih, Sonja and Müller, Klaus-Robert and Kübler, Andrea},
year = {2012},
pages = {80--86}
}
@article{szucs_functional_2012,
title = {Functional definition of the {N}450 event-related brain potential marker of conflict processing: a numerical stroop study},
volume = {13},
issn = {1471-2202},
shorttitle = {Functional definition of the {N}450 event-related brain potential marker of conflict processing},
url = {http://link.springer.com/article/10.1186/1471-2202-13-35},
doi = {10.1186/1471-2202-13-35},
abstract = {Background Several conflict processing studies aimed to dissociate neuroimaging phenomena related to stimulus and response conflict processing. However, previous studies typically did not include a paradigm-independent measure of either stimulus or response conflict. Here we have combined electro-myography (EMG) with event-related brain potentials (ERPs) in order to determine whether a particularly robust marker of conflict processing, the N450 ERP effect usually related to the activity of the Anterior Cingulate Cortex (ACC), is related to stimulus- or to response-conflict processing. EMG provided paradigm-independent measure of response conflict. In a numerical Stroop paradigm participants compared pairs of digits and pressed a button on the side where they saw the larger digit. 50\% of digit-pairs were preceded by an effective cue which provided accurate information about the required response. 50\% of trials were preceded by a neutral cue which did not communicate the side of response. Results EMG showed that response conflict was significantly larger in neutrally than in effectively cued trials. The N450 was similar when response conflict was high and when it was low. Conclusions We conclude that the N450 is related to stimulus or abstract, rather than to response conflict detection/resolution. Findings may enable timing ACC conflict effects.},
language = {en},
number = {1},
urldate = {2016-04-26},
journal = {BMC Neuroscience},
author = {Szűcs, Dénes and Soltész, Fruzsina},
month = mar,
year = {2012},
pages = {1--14},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/2F2QF23B/Szűcs and Soltész - 2012 - Functional definition of the N450 event-related br.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/52HMEFHE/1471-2202-13-35.html:text/html}
}
@article{lu_regularized_2010,
title = {Regularized {Common} {Spatial} {Pattern} {With} {Aggregation} for {EEG} {Classification} in {Small}-{Sample} {Setting}},
volume = {57},
number = {12},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Lu, Haiping and Eng, How-Lung and Guan, Cuntai and Plataniotis, K.N. and Venetsanopoulos, A.N.},
year = {2010},
pages = {2936--2946}
}
@inproceedings{grandvalet_anisotropic_2000,
title = {Anisotropic {Noise} {Injection} for {Input} {Variables} {Relevance} {Determination}},
booktitle = {{IEEE} {TRANSACTIONS} {ON} {NEURAL} {NETWORKS}},
publisher = {Springer},
author = {Grandvalet, Yves},
year = {2000},
pages = {463--468}
}
@article{zou_eeg_2010,
title = {{EEG} feature extraction and pattern classification based on motor imagery in brain-computer interface},
journal = {Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on},
author = {Zou, Ling and Wang, Xinguang and Shi, Guodong and Ma, Zhenghua},
year = {2010},
pages = {536--541}
}
@article{krusienski_critical_2011,
title = {Critical issues in state-of-the-art brain–computer interface signal processing},
volume = {8},
issn = {1741-2552},
url = {http://stacks.iop.org/1741-2552/8/i=2/a=025002},
doi = {10.1088/1741-2560/8/2/025002},
abstract = {This paper reviews several critical issues facing signal processing for brain–computer interfaces (BCIs) and suggests several recent approaches that should be further examined. The topics were selected based on discussions held during the 4th International BCI Meeting at a workshop organized to review and evaluate the current state of, and issues relevant to, feature extraction and translation of field potentials for BCIs. The topics presented in this paper include the relationship between electroencephalography and electrocorticography, novel features for performance prediction, time-embedded signal representations, phase information, signal non-stationarity, and unsupervised adaptation.},
language = {en},
number = {2},
urldate = {2016-05-11},
journal = {Journal of Neural Engineering},
author = {Krusienski, Dean J. and Grosse-Wentrup, Moritz and Galán, Ferran and Coyle, Damien and Miller, Kai J. and {Elliott Forney} and Anderson, Charles W.},
year = {2011},
pages = {025002},
file = {IOP Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/CN9N6GRN/Krusienski et al. - 2011 - Critical issues in state-of-the-art brain–computer.pdf:application/pdf}
}
@article{sutter_brain_1992,
title = {The brain response interface: communication through visually-induced electrical brain responses},
volume = {15},
shorttitle = {The brain response interface},
url = {http://www.sciencedirect.com/science/article/pii/0745713892900457},
number = {1},
urldate = {2016-04-15},
journal = {Journal of Microcomputer Applications},
author = {Sutter, Erich E.},
year = {1992},
pages = {31--45},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BJATJAQK/0745713892900457.html:text/html}
}
@article{khorshidtalab_eeg_2011,
title = {{EEG} signal classification for real-time brain-computer interface applications: {A} review},
journal = {Mechatronics (ICOM), 2011 4th International Conference On},
author = {Khorshidtalab, A. and Salami, M. J. E.},
year = {2011},
pages = {1--7}
}
@article{badcock_validation_2013,
title = {Validation of the {Emotiv} {EPOC}® {EEG} gaming system for measuring research quality auditory {ERPs}},
volume = {1},
url = {https://peerj.com/articles/38/?utm_source=blog&utm_medium=web&utm_term=videooculography&utm_content=Article38&utm_campaign=MostCitedBlog},
urldate = {2016-05-31},
journal = {PeerJ},
author = {Badcock, Nicholas A. and Mousikou, Petroula and Mahajan, Yatin and de Lissa, Peter and Thie, Johnson and McArthur, Genevieve},
year = {2013},
pages = {e38},
file = {[HTML] from peerj.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/D96W4X28/38.html:text/html}
}
@article{wang_lead_2004,
title = {Lead selection for {SSVEP}-based brain-computer interface},
volume = {2},
journal = {Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE},
author = {Wang, Yijun and Zhang, Zhiguang and Gao, Xiaorong and Gao, Shangkai},
year = {2004},
pages = {4507--4510}
}
@article{cohen_coefficient_1960,
title = {A {Coefficient} of {Agreement} for {Nominal} {Scales}},
volume = {20},
number = {1},
journal = {Educational and Psychological Measurement},
author = {Cohen, J.},
year = {1960},
pages = {37}
}
@article{teli_nonlinear_2009,
title = {Nonlinear dimensionality reduction of electroencephalogram ({EEG}) for {Brain} {Computer} interfaces},
journal = {Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE},
author = {Teli, Mohammad Nayeem and Anderson, Charles},
year = {2009},
pages = {2486--2489}
}
@article{townsend_pushing_2016,
title = {Pushing the {P}300-based brain–computer interface beyond 100 bpm: extending performance guided constraints into the temporal domain},
volume = {13},
issn = {1741-2552},
shorttitle = {Pushing the {P}300-based brain–computer interface beyond 100 bpm},
url = {http://stacks.iop.org/1741-2552/13/i=2/a=026024},
doi = {10.1088/1741-2560/13/2/026024},
abstract = {Objective. A new presentation paradigm for the P300-based brain–computer interface (BCI) referred to as the ‘asynchronous paradigm’ (ASP) is introduced and studied. It is based on the principle of performance guided constraints (Townsend et al 2012 Neurosci. Lett. 531 [http://dx.doi.org/10.1016/j.neulet.2012.08.041] 63–8 ) extended from the spatial domain into the temporal domain. The traditional constraint of flashing targets in predefined constant epochs of time is eliminated and targets flash asynchronously with timing based instead on constraints intended to improve performance. Approach. We propose appropriate temporal constraints to derive the ASP and compare its performance to that of the ‘checkerboard paradigm’ (CBP), which has previously been shown to be superior to the standard ‘row/column paradigm’ introduced by Farwell and Donchin (1988 Electroencephalogr. Clin. Neurophysiol. 70 [http://dx.doi.org/10.1016/0013-4694(88)90149-6] 510–23 ). Ten participants were tested in the ASP and CBP conditions both with traditional flashing items and with flashing faces in place of the targets (see Zhang et al 2012 J. Neural Eng. 9 [http://dx.doi.org/10.1088/1741-2560/9/2/026018] 026018 ; Kaufmann and Kübler 2014 J. Neural Eng. 11 [http://] ; Chen et al 2015 J. Neurosci. Methods 239 [http://dx.doi.org/10.1016/j.jneumeth.2014.10.002] 18–27 ). Eleven minutes of calibration data were used as input to a stepwise linear discriminant analysis to derive classification coefficients used for online classification. Main results. Accuracy was consistently high for both paradigms (87\% and 93\%) while information transfer rate was 45\% higher for the ASP than the CBP. In a free spelling task, one subject spelled a 66 character sentence (from a 72 item matrix) with 100\% accuracy in 3 min and 24 s demonstrating a practical throughput of 120 bits per minute (bpm) with a theoretical upper bound of 258 bpm. The subject repeated the task three times in a row without error. Significance. This work represents an advance in P300 speller technology and raises the ceiling that was being reached on P300-based BCIs. Most importantly, the research presented here is a novel and effective general strategy for organising timing for flashing items. The ASP is only one possible implementation of this work since in general it can be used to describe all previous existing presentation paradigms as well as any possible new ones. This may be especially important for people with neuromuscular disabilities.},
language = {en},
number = {2},
urldate = {2016-04-28},
journal = {Journal of Neural Engineering},
author = {Townsend, G. and Platsko, V.},
year = {2016},
pages = {026024}
}
@inproceedings{barachant_common_2010,
title = {Common spatial pattern revisited by {Riemannian} geometry},
booktitle = {Multimedia {Signal} {Processing} ({MMSP}), 2010 {IEEE} {International} {Workshop} on},
publisher = {IEEE},
author = {Barachant, Alexandre and Bonnet, Stéphane and Congedo, Marco and Jutten, Christian},
year = {2010},
pages = {472--476}
}
@inproceedings{cherian_efficient_2011,
title = {Efficient similarity search for covariance matrices via the {Jensen}-{Bregman} {LogDet} divergence},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6126523},
urldate = {2016-06-23},
booktitle = {2011 {International} {Conference} on {Computer} {Vision}},
publisher = {IEEE},
author = {Cherian, Anoop and Sra, Suvrit and Banerjee, Arindam and Papanikolopoulos, Nikolaos},
year = {2011},
pages = {2399--2406},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/KF7TS7G2/Cherian et al. - 2011 - Efficient similarity search for covariance matrice.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/EZENUHA4/login.html:text/html}
}
@article{koles_spatial_1990,
title = {Spatial patterns underlying population differences in the background {EEG}},
volume = {2},
url = {http://link.springer.com/article/10.1007/BF01129656},
number = {4},
urldate = {2016-05-20},
journal = {Brain topography},
author = {Koles, Zoltan J. and Lazar, Michael S. and Zhou, Steven Z.},
year = {1990},
pages = {275--284},
file = {[PDF] from springer.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/H2CM2IDI/Koles et al. - 1990 - Spatial patterns underlying population differences.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/DGHBETQP/BF01129656.html:text/html}
}
@article{liu_novel_2011,
title = {Novel feature of the {EEG} based motor imagery {BCI} system: {Degree} of imagery},
journal = {System Science and Engineering (ICSSE), 2011 International Conference on},
author = {Liu, Yi Hung and Cheng, Ching An and Huang, Han-Pang},
year = {2011},
pages = {515--520}
}
@article{pfurtscheller_event-related_1977,
title = {Event-related cortical desynchronization detected by power measurements of scalp {EEG}},
volume = {42},
number = {6},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Pfurtscheller, G. and Aranibar, A.},
year = {1977},
pages = {817--826}
}
@article{fraga_gonzalez_brain-potential_2014,
title = {Brain-potential analysis of visual word recognition in dyslexics and typically reading children},
volume = {8},
url = {http://journal.frontiersin.org/article/10.3389/fnhum.2014.00474/full},
doi = {10.3389/fnhum.2014.00474},
abstract = {The specialization of visual brain areas for fast processing of printed words plays an important role in the acquisition of reading skills. Dysregulation of these areas may be among the deficits underlying developmental dyslexia. The present study examines the specificity of word activation in dyslexic children in 3rd grade by comparing early components of brain potentials elicited by visually presented words vs. strings of meaningless letter-like symbols. Results showed a more pronounced N1 component for words compared to symbols for both groups. The dyslexic group revealed larger left-lateralized, word-specific N1 responses than the typically reading group. Furthermore, positive correlations between N1 amplitudes and reading fluency were found in the dyslexic group. Our results support the notion of N1 as a sensitive index of visual word processing involved in reading fluency.},
urldate = {2016-03-31},
journal = {Frontiers in Human Neuroscience},
author = {Fraga González, Gorka and Žarić, Gojko and Tijms, Jurgen and Bonte, Milene and Blomert, Leo and van der Molen, Maurits},
year = {2014},
keywords = {developmental dyslexia, event-related potentials, N1, Parieto-occipital brain region, reading fluency, visual attention, visual word recognition},
pages = {474}
}
@article{ritter_averaged_1969,
title = {Averaged evoked responses in vigilance and discrimination: a reassessment},
volume = {164},
number = {3877},
journal = {Science},
author = {Ritter, W and Vaughan, H G},
year = {1969},
pages = {326--8}
}
@inproceedings{jayasumana_kernel_2013,
title = {Kernel methods on the {Riemannian} manifold of symmetric positive definite matrices},
booktitle = {Computer {Vision} and {Pattern} {Recognition} ({CVPR}), 2013 {IEEE} {Conference} on},
publisher = {IEEE},
author = {Jayasumana, Sadeep and Hartley, Richard and Salzmann, Mathieu and Li, Hongdong and Harandi, Mehrtash},
year = {2013},
pages = {73--80}
}
@book{duda_pattern_2001,
edition = {2},
title = {Pattern classification},
isbn = {978-0-471-05669-0},
publisher = {Wiley},
author = {Duda, R. and Hart, P. and Stork, D},
year = {2001}
}
@article{karcher_riemannian_2014,
title = {Riemannian center of mass and so called karcher mean},
url = {http://arxiv.org/abs/1407.2087},
urldate = {2016-06-14},
journal = {arXiv preprint arXiv:1407.2087},
author = {Karcher, Hermann},
year = {2014},
file = {[PDF] from arxiv.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/SRANEBJ9/Karcher - 2014 - Riemannian center of mass and so called karcher me.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/M8INJ7KJ/1407.html:text/html}
}
@article{wolpaw_multichannel_1994,
title = {Multichannel {EEG}-based brain-computer communication},
volume = {90},
issn = {0013-4694},
url = {http://www.sciencedirect.com/science/article/pii/001346949490135X},
doi = {10.1016/0013-4694(94)90135-X},
abstract = {Individuals who are paralyzed or have other severe movement disorders often need alternative means for communicating with and controlling their environments. In this study, human subjects learned to use two channels of bipolar EEG activity to control 2-dimensional movement of a cursor on a computer screen. Amplitudes of 8–12 Hz activity in the EEG recorded from the scalp across right and left central sulci were determined by fast Fourier transform and combined to control vertical and horizontal cursor movements simultaneously. This independent control of two separate EEG channels cannot be attributed to a non-specific change in brain activity and appeared to be specific to the mu rhythm frequency range. With further development, multichannel EEG-based communication may prove of significant value to those with severe motor disabilities.},
number = {6},
urldate = {2016-03-09},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Wolpaw, Jonathan R. and McFarland, Dennis J.},
month = jun,
year = {1994},
keywords = {Assistive communication, Electroencephalography, Mu rhythm, Operant conditioning, Prosthesis, Rehabilitation, Sensorimotor cortex},
pages = {444--449},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/TXNGIMIR/Wolpaw and McFarland - 1994 - Multichannel EEG-based brain-computer communicatio.pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/CDU88DDE/001346949490135X.html:text/html}
}
@article{foldes_meg-based_2015,
title = {{MEG}-based neurofeedback for hand rehabilitation},
volume = {12},
issn = {1743-0003},
url = {http://dx.doi.org/10.1186/s12984-015-0076-7},
doi = {10.1186/s12984-015-0076-7},
abstract = {Providing neurofeedback (NF) of motor-related brain activity in a biologically-relevant and intuitive way could maximize the utility of a brain-computer interface (BCI) for promoting therapeutic plasticity. We present a BCI capable of providing intuitive and direct control of a video-based grasp.},
urldate = {2016-04-19},
journal = {Journal of NeuroEngineering and Rehabilitation},
author = {Foldes, Stephen T. and Weber, Douglas J. and Collinger, Jennifer L.},
year = {2015},
keywords = {brain-computer interface, Magnetoencephalography, Neurofeedback, Neuroplasticity, Rehabilitation, Spinal Cord Injury},
pages = {85},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/NW5TZJW4/Foldes et al. - 2015 - MEG-based neurofeedback for hand rehabilitation.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/D4A9I7NC/s12984-015-0076-7.html:text/html}
}
@article{hill_classifying_2006,
title = {Classifying {EEG} and {ECoG} {Signals} without {Subject} {Training} for {Fast} {BCI} {Implementation}: {Comparison} of {Non}-{Paralysed} and {Completely} {Paralysed} {Subjects}},
volume = {14},
number = {2},
journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
author = {Hill, NJ and Lal, TN and Schröder, M and Hinterberger, T and Wilhelm, B and Nijboer, F and Mochty, U and Widman, G and Elger, CE and Schölkopf, B and Kübler, A and Birbaumer, N},
year = {2006},
pages = {183--186}
}
@inproceedings{simard_best_2003,
title = {Best practices for convolutional neural networks applied to visual document analysis},
volume = {2},
booktitle = {2013 12th {International} {Conference} on {Document} {Analysis} and {Recognition}},
publisher = {IEEE Computer Society},
author = {Simard, Patrice Y and Steinkraus, Dave and Platt, John C},
year = {2003},
pages = {958--958}
}
@article{hyvarinen_a._and_oja_e._independent_2000,
title = {Independent component analysis: algorithms and applications.},
volume = {13},
number = {4-5},
journal = {Neural Netw},
author = {{Hyvärinen, A. and Oja, E.}},
year = {2000},
pages = {411--430}
}
@article{aloise_covert_2012,
title = {A covert attention {P}300-based brain–computer interface: {Geospell}},
volume = {55},
shorttitle = {A covert attention {P}300-based brain–computer interface},
url = {http://www.tandfonline.com/doi/abs/10.1080/00140139.2012.661084},
number = {5},
urldate = {2016-04-28},
journal = {Ergonomics},
author = {Aloise, Fabio and Aricò, Pietro and Schettini, Francesca and Riccio, Angela and Salinari, Serenella and Mattia, Donatella and Babiloni, Fabio and Cincotti, Febo},
year = {2012},
pages = {538--551},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/48UAZTZZ/00140139.2012.html:text/html}
}
@article{huang_framework_2011,
title = {A framework for rapid visual image search using single-trial brain evoked responses},
volume = {74},
number = {12-13},
journal = {Neurocomputing},
author = {Huang, Yonghong and Erdogmus, Deniz and Pavel, Misha and Mathan, Santosh and Hild, Kenneth E.},
year = {2011},
pages = {2041--2051}
}
@inproceedings{yang_automatic_2012,
title = {Automatic selection of the number of spatial filters for motor-imagery {BCI}},
abstract = {Common Spatial Pattern (CSP) is widely used for constructing spatial filters to extract features for motor-imagery-based BCI. One main parameter in CSP-based classification is the number of spatial filters used. An automatic method relying on Rayleigh quotient is presented to estimate its optimal value for each subject. Based on an existing dataset, we validate the contribution of the proposed method through a study of the effect of this parameter on the classification performance. The evaluation on testing data shows that the estimated subject-specific optimal values yield better performances than the recommanded value in the literature.},
booktitle = {European {Symposium} on {Artificial} {Neural} {Networks} ({ESANN})},
author = {Yang, Y. and Chevallier, S. and Wiart, J. and Bloch, I.},
editor = {Verleysen, M.},
year = {2012},
pages = {109--114}
}
@inproceedings{kalunga_ssvep_2013,
title = {{SSVEP} enhancement based on {Canonical} {Correlation} {Analysis} to improve {BCI} performances},
doi = {10.1109/AFRCON.2013.6757776},
abstract = {Brain Computer Interfaces (BCI) rely on brain waves signal, such as electro-encephalogram (EEG) recording, to endow a disabled user with non-muscular communication. Given the very low signal-to-noise ratio of EEG, a signal enhancement phase is crucial for ensuring decent performances in BCI systems. Several methods have been proposed for EEG signal enhancement, such as Independent Component Analysis, Common Spatial Pattern, and Principal Component Analysis. We show that Canonical Correlation Analysis (CCA), initially introduced to SSVEP-based BCI as a feature extraction method, is a good candidate for such preprocessing state. Evaluation is performed on a recording from 5 subjects during a BCI task based on Steady-State Visual Evoked Potentials (SSVEP). The authors demonstrate that CCA significantly improves classification performances in SSVEP-based BCIs.},
booktitle = {{AFRICON}, 2013},
author = {Kalunga, E. and Djouani, K. and Hamam, Y. and Chevallier, S. and Monacelli, E.},
month = sep,
year = {2013},
keywords = {Ash, BCI performances, brain-computer interfaces, brain computer interfaces, brain waves signal, canonical correlation analysis, classification performances, common spatial pattern, Correlation, disabled user, EEG signal enhancement phase, electroencephalogram recording, Electroencephalography, feature extraction, feature extraction method, independent component analysis, medical signal processing, nonmuscular communication, preprocessing state, principal component analysis, signal classification, signal denoising, SSVEP enhancement, steady-state visual evoked potentials, Support vector machines, Training, very low signal-to-noise ratio, visual evoked potentials, Visualization},
pages = {1--5},
file = {IEEE Xplore Abstract Record:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/RJGQ8N6G/login.html:text/html}
}
@book{niedermeyer_electroencephalography:_2005,
title = {Electroencephalography: {Basic} {Principles}, {Clinical} {Applications}, and {Related} {Fields}},
isbn = {978-0-7817-5126-1},
shorttitle = {Electroencephalography},
abstract = {Established in 1982 as the leading reference on electroencephalography, Drs. Niedermeyer's and Lopes da Silva's text is now in its thoroughly updated Fifth Edition. An international group of experts provides comprehensive coverage of the neurophysiologic and technical aspects of EEG, evoked potentials, and magnetoencephalography, as well as the clinical applications of these studies in neonates, infants, children, adults, and older adults. This edition includes digital EEG and advances in areas such as neurocognition. Three new chapters cover the topics of Ultra-Fast EEG Frequencies, Ultra-Slow Activity, and Cortico-Muscular Coherence. Hundreds of EEG tracings and other illustrations complement the text.},
language = {en},
publisher = {Lippincott Williams \& Wilkins},
author = {Niedermeyer, Ernst and Silva, F. H. Lopes da},
year = {2005},
keywords = {Medical / Diagnosis, Medical / Neurology}
}
@article{henson_parametric_2011,
title = {A parametric empirical {Bayesian} framework for the {EEG}/{MEG} inverse problem: generative models for multi-subject and multi-modal integration},
volume = {5},
shorttitle = {A parametric empirical {Bayesian} framework for the {EEG}/{MEG} inverse problem},
url = {http://journal.frontiersin.org/article/10.3389/fnhum.2011.00076/full},
doi = {10.3389/fnhum.2011.00076},
abstract = {We review recent methodological developments within a parametric empirical Bayesian (PEB) framework for reconstructing intracranial sources of extracranial electroencephalographic (EEG) and magnetoencephalographic (MEG) data under linear Gaussian assumptions. The PEB framework offers a natural way to integrate multiple constraints (spatial priors) on this inverse problem, such as those derived from different modalities (e.g., from functional magnetic resonance imaging, fMRI) or from multiple replications (e.g., subjects). Using variations of the same basic generative model, we illustrate the application of PEB to three cases: (1) symmetric integration (fusion) of MEG and EEG; (2) asymmetric integration of MEG or EEG with fMRI, and (3) group-optimization of spatial priors across subjects. We evaluate these applications on multi-modal data acquired from 18 subjects, focusing on energy induced by face perception within a time–frequency window of 100–220 ms, 8–18 Hz. We show the benefits of multi-modal, multi-subject integration in terms of the model evidence and the reproducibility (over subjects) of cortical responses to faces.},
urldate = {2016-04-19},
journal = {Frontiers in Human Neuroscience},
author = {Henson, Richard N. and Wakeman, Daniel G. and Litvak, Vladimir and Friston, Karl J.},
year = {2011},
keywords = {bioelectromagnetic signals, data fusion, neuroimaging, source reconstruction},
pages = {76}
}
@article{sutton_evoked-potential_1965,
title = {Evoked-potential {Correlates} of {Stimulus} {Uncertainty}},
volume = {150},
journal = {Science},
author = {Sutton, S. and Braren, M. and Zubin, J. and John, E. R.},
year = {1965},
pages = {1187--1188}
}
@article{kennedy_computer_2004,
title = {Computer control using human intracortical local field potentials},
volume = {12},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1333049},
number = {3},
urldate = {2016-04-18},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {Kennedy, Philip R. and Kirby, M. Todd and Moore, Melody M. and King, Brandon and Mallory, Adon},
year = {2004},
pages = {339--344},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/IPHSCQN8/login.html:text/html}
}
@article{vidal_toward_1973,
title = {Toward direct brain-computer communication.},
volume = {2},
number = {1},
journal = {Annual review of biophysics and bioengineering},
author = {Vidal, J. J.},
year = {1973},
pages = {157--180}
}
@inproceedings{acqualagna_novel_2010,
title = {A novel brain-computer interface based on the rapid serial visual presentation paradigm},
doi = {10.1109/IEMBS.2010.5626548},
abstract = {Most present-day visual brain computer interfaces (BCIs) suffer from the fact that they rely on eye movements, are slow-paced, or feature a small vocabulary. As a potential remedy, we explored a novel BCI paradigm consisting of a central rapid serial visual presentation (RSVP) of the stimuli. It has a large vocabulary and realizes a BCI system based on covert non-spatial selective visual attention. In an offline study, eight participants were presented sequences of rapid bursts of symbols. Two different speeds and two different color conditions were investigated. Robust early visual and P300 components were elicited time-locked to the presentation of the target. Offline classification revealed a mean accuracy of up to 90\% for selecting the correct symbol out of 30 possibilities. The results suggest that RSVP-BCI is a promising new paradigm, also for patients with oculomotor impairments.},
booktitle = {2010 {Annual} {International} {Conference} of the {IEEE} {Engineering} in {Medicine} and {Biology}},
author = {Acqualagna, L. and Treder, M. S. and Schreuder, M. and Blankertz, B.},
month = aug,
year = {2010},
keywords = {Accuracy, Adult, Biomedical Engineering, Brain, brain-computer interface, brain-computer interfaces, central RSVP paradigm, Computers, covert nonspatial selective visual attention, Electric potential, Electrodes, Electroencephalography, Event-Related Potentials, P300, Evoked Potentials, Female, Humans, Image color analysis, Male, medical signal processing, neurophysiology, oculomotor impairments, rapid serial visual presentation, rapid symbol bursts, Reproducibility of Results, RSVP-BCI, Signal Processing, Computer-Assisted, Software, Time Factors, User-Computer Interface, visual BCI, visual evoked potentials, Visualization, Vocabulary},
pages = {2686--2689},
file = {IEEE Xplore Abstract Record:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/AJHTUTDN/login.html:text/html}
}
@inproceedings{martin_fast_2012,
title = {Fast calibration of hand movement-based interface for arm exoskeleton control},
abstract = {Several muscular degenerative diseases alter motor abilities of large muscles but spare smaller muscles, e.g. keeping hand motor skills relatively unaffected while upper limbs ones are altered. Thus, hand movements could be be used to control an arm exoskeleton for rehabilitation and assistive purpose. Using an infra-red sensors (IR) based interface for the exoskeleton control, this paper describes the learning part of the system, endowing the system with a fast online calibration and adaptation abilities. This learning component shows good results and have been successfully implemented on the real system.},
booktitle = {European {Symposium} on {Artificial} {Neural} {Networks} ({ESANN})},
author = {Martin, Hugo and Chevallier, Sylvain and Monacelli, Eric},
year = {2012},
pages = {573--578}
}
@article{wilson_ecog_2006,
title = {{ECoG} factors underlying multimodal control of a brain-computer interface},
volume = {14},
number = {2},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {Wilson, J.A. and Felton, E.A. and Garell, P.C. and Schalk, G. and Williams, J.C.},
year = {2006},
pages = {246--250}
}
@inproceedings{wang_review_2015,
title = {A review on transfer learning for brain-computer interface classification},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7288989},
urldate = {2016-06-01},
booktitle = {Information {Science} and {Technology} ({ICIST}), 2015 5th {International} {Conference} on},
publisher = {IEEE},
author = {Wang, Peitao and Lu, Jun and Zhang, Bin and Tang, Zeng},
year = {2015},
pages = {315--322},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/FM4BDKZG/login.html:text/html}
}
@article{costagliola_recognition_2009,
title = {Recognition and classification of {P}300s in {EEG} signals by means of feature extraction using wavelet decomposition},
journal = {Neural Networks, 2009. IJCNN 2009. International Joint Conference on},
author = {Costagliola, S. and Seno, B.D. and Matteucci, M.},
year = {2009},
pages = {597--603}
}
@article{santhanam_high-performance_2006,
title = {A high-performance brain–computer interface},
volume = {442},
copyright = {© 2006 Nature Publishing Group},
issn = {0028-0836},
url = {http://www.nature.com/nature/journal/v442/n7099/abs/nature04968.html},
doi = {10.1038/nature04968},
abstract = {Recent studies have demonstrated that monkeys and humans can use signals from the brain to guide computer cursors. Brain–computer interfaces (BCIs) may one day assist patients suffering from neurological injury or disease, but relatively low system performance remains a major obstacle. In fact, the speed and accuracy with which keys can be selected using BCIs is still far lower than for systems relying on eye movements. This is true whether BCIs use recordings from populations of individual neurons using invasive electrode techniques or electroencephalogram recordings using less- or non-invasive techniques. Here we present the design and demonstration, using electrode arrays implanted in monkey dorsal premotor cortex, of a manyfold higher performance BCI than previously reported. These results indicate that a fast and accurate key selection system, capable of operating with a range of keyboard sizes, is possible (up to 6.5 bits per second, or 15 words per minute, with 96 electrodes). The highest information throughput is achieved with unprecedentedly brief neural recordings, even as recording quality degrades over time. These performance results and their implications for system design should substantially increase the clinical viability of BCIs in humans.},
language = {en},
number = {7099},
urldate = {2016-04-18},
journal = {Nature},
author = {Santhanam, Gopal and Ryu, Stephen I. and Yu, Byron M. and Afshar, Afsheen and Shenoy, Krishna V.},
month = jul,
year = {2006},
pages = {195--198},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ABPQCZMW/Santhanam et al. - 2006 - A high-performance brain–computer interface.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/3P855CHJ/nature04968.html:text/html}
}
@article{homer_implants_2013,
title = {Implants and {Decoding} for {Intracortical} {Brain} {Computer} {Interfaces}},
volume = {15},
issn = {1523-9829},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3985135/},
doi = {10.1146/annurev-bioeng-071910-124640},
abstract = {Intracortical brain computer interfaces (iBCIs) are being developed to enable a person to drive an output device, such as a computer cursor, directly from their neural activity. One goal of the technology is to help people with severe paralysis or limb loss. Key elements of an iBCI are the implanted sensor that records the neural signals and the software which decodes the user’s intended movement from those signals. Here, we focus on recent advances in these two areas, with special attention being placed on contributions that are or may soon be adopted by the iBCI research community. We discuss how these innovations increase the technology’s capability, accuracy, and longevity, all important steps that are expanding the range of possible future clinical applications.},
urldate = {2016-04-15},
journal = {Annual review of biomedical engineering},
author = {Homer, Mark L. and Nurmikko, Arto V. and Donoghue, John P. and Hochberg, Leigh R.},
year = {2013},
pmid = {23862678},
pmcid = {PMC3985135},
pages = {383--405},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/PPG3NCQM/Homer et al. - 2013 - Implants and Decoding for Intracortical Brain Comp.pdf:application/pdf}
}
@article{popescu_single_2007,
title = {Single trial classification of motor imagination using 6 dry {EEG} electrodes},
volume = {2},
url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0000637},
number = {7},
urldate = {2016-06-01},
journal = {PloS one},
author = {Popescu, Florin and Fazli, Siamac and Badower, Yakob and Blankertz, Benjamin and Müller, Klaus-R.},
year = {2007},
pages = {e637},
file = {[HTML] from plos.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/2KN7GT94/article.html:text/html}
}
@article{lenhardt_adaptive_2008,
title = {An {Adaptive} {P}300-{Based} {Online} {Brain} {Computer} {Interface}},
volume = {16},
number = {2},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {Lenhardt, A. and Kaper, M. and Ritter, H.J.},
year = {2008},
pages = {121--130}
}
@inproceedings{li_eeg_2009,
title = {{EEG} signal classification based on a {Riemannian} distance measure},
booktitle = {Science and {Technology} for {Humanity} ({TIC}-{STH}), 2009 {IEEE} {Toronto} {International} {Conference}},
publisher = {IEEE},
author = {Li, Yili and Wong, Kon Max and De Bruin, H},
year = {2009},
pages = {268--273}
}
@article{ferrez_error-related_2008,
title = {Error-{Related} {EEG} {Potentials} {Generated} {During} {Simulated} {Brain}-{Computer} {Interaction}},
volume = {55},
number = {3},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Ferrez, P.W. and del R. Millan, J.},
year = {2008},
pages = {923--929}
}
@article{naseer_classification_2013,
title = {Classification of functional near-infrared spectroscopy signals corresponding to the right- and left-wrist motor imagery for development of a brain–computer interface},
volume = {553},
issn = {03043940},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0304394013007544},
doi = {10.1016/j.neulet.2013.08.021},
language = {en},
urldate = {2016-04-19},
journal = {Neuroscience Letters},
author = {Naseer, Noman and Hong, Keum-Shik},
month = oct,
year = {2013},
pages = {84--89}
}
@article{wang_improving_2013,
title = {Improving {Brain}-computer {Interfaces} {Using} {Independent} {Component} {Analysis}},
journal = {Towards Practical Brain-Computer Interfaces},
author = {Wang, Yijun and Jung, Tzyy-Ping},
year = {2013},
pages = {67--83}
}
@article{grosse-wentrup_multiclass_2008,
title = {Multiclass common spatial patterns and information theoretic feature extraction},
volume = {55},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4473042},
number = {8},
urldate = {2016-05-21},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Grosse-Wentrup, Moritz and Buss, Martin},
year = {2008},
pages = {1991--2000},
file = {[PDF] from mpg.de:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/EDMHKDER/Grosse-Wentrup and Buss - 2008 - Multiclass common spatial patterns and information.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QVE4AC22/login.html:text/html}
}
@article{sadeh_why_2010,
title = {Why is the {N}170 enhanced for inverted faces? {An} {ERP} competition experiment},
volume = {53},
shorttitle = {Why is the {N}170 enhanced for inverted faces?},
url = {http://www.sciencedirect.com/science/article/pii/S1053811910008736},
number = {2},
urldate = {2016-02-01},
journal = {Neuroimage},
author = {Sadeh, Boaz and Yovel, Galit},
year = {2010},
pages = {782--789},
file = {[PDF] à partir de tau.ac.il:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/MWQFAQ6J/Sadeh and Yovel - 2010 - Why is the N170 enhanced for inverted faces An ER.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/MAMZMWBJ/S1053811910008736.html:text/html}
}
@article{eimerca_erp_????,
title = {An {ERP} study on the time course of emotional face processing},
url = {http://www.brainb.psyc.bbk.ac.uk/PDF/NR2002.PDF},
urldate = {2016-02-01},
author = {EimerCA, Martin and Holmes, Amanda},
file = {[PDF] from bbk.ac.uk:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/CT86NXXA/EimerCA and Holmes - An ERP study on the time course of emotional face .pdf:application/pdf}
}
@misc{_mensia_????,
title = {Mensia {Technologies}},
url = {http://www.mensiatech.com/},
urldate = {2016-03-09},
file = {Mensia Technologies:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/6Q5GMMGB/www.mensiatech.com.html:text/html}
}
@inproceedings{pascal_theoretical_2005,
title = {Theoretical analysis of an improved covariance matrix estimator in non-{Gaussian} noise},
volume = {4},
booktitle = {{IEEE} {International} {Conference} on {Acoustics}, {Speech}, and {Signal} {Processing} ({ICASSP}).},
author = {Pascal, F. and Forster, P. and Ovarlez, J. -P and Arzabal, P.},
month = mar,
year = {2005}
}
@article{yin_novel_2013,
title = {A novel hybrid {BCI} speller based on the incorporation of {SSVEP} into the {P}300 paradigm},
volume = {10},
abstract = {Objective. Although extensive studies have shown improvement in spelling accuracy, the conventional P300 speller often exhibits errors, which occur in almost the same row or column relative to the target. To address this issue, we propose a novel hybrid brain-computer interface (BCI) approach by incorporating the steady-state visual evoked potential (SSVEP) into the conventional P300 paradigm. Approach. We designed a periodic stimuli mechanism and superimposed it onto the P300 stimuli to increase the difference between the symbols in the same row or column. Furthermore, we integrated the random flashings and periodic flickers to simultaneously evoke the P300 and SSVEP, respectively. Finally, we developed a hybrid detection mechanism based on the P300 and SSVEP in which the target symbols are detected by the fusion of three-dimensional, time-frequency features. Main results. The results obtained from 12 healthy subjects show that an online classification accuracy of 93.85\% and information transfer rate of 56.44 bit/min were achieved using the proposed BCI speller in only a single trial. Specifically, 5 of the 12 subjects exhibited an information transfer rate of 63.56 bit/min with an accuracy of 100\%. Significance . The pilot studies suggested that the proposed BCI speller could achieve a better and more stable system performance compared with the conventional P300 speller, and it is promising for achieving quick spelling in stimulus-driven BCI applications.},
number = {2},
journal = {Journal of Neural Engineering},
author = {Yin, Erwei and Zhou, Zongtan and Jiang, Jun and Chen, Fanglin and Liu, Yadong and Hu, Dewen},
year = {2013}
}
@article{schlogl_characterization_2005,
title = {Characterization of four-class motor imagery {EEG} data for the {BCI}-competition 2005},
volume = {2},
number = {4},
journal = {Journal of Neural Engineering},
author = {Schlögl, Alois and Lee, Felix and Bischof, Horst and Pfurtscheller, Gert},
year = {2005},
pages = {14--22}
}
@article{stapleton_endogenous_1987,
title = {Endogenous potentials evoked in simple cognitive tasks: depth components and task correlates},
volume = {67},
number = {1},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Stapleton, J. M. and Halgren, E.},
year = {1987},
pages = {44--52}
}
@article{ma_research_2011,
title = {The research of brain-computer interface based on {AAR} parameters and neural networks classifier},
volume = {4},
journal = {Computer Science and Network Technology (ICCSNT), 2011 International Conference on},
author = {Ma, Xin},
year = {2011},
pages = {2561--2564}
}
@article{nguyen_superior_2014,
title = {The superior temporal sulcus and the {N}170 during face processing: {Single} trial analysis of concurrent {EEG}–{fMRI}},
volume = {86},
shorttitle = {The superior temporal sulcus and the {N}170 during face processing},
url = {http://www.sciencedirect.com/science/article/pii/S1053811913010707},
urldate = {2016-02-01},
journal = {NeuroImage},
author = {Nguyen, Vinh T. and Cunnington, Ross},
year = {2014},
keywords = {N170, Single trial},
pages = {492--502},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/VZDW72D4/S1053811913010707.html:text/html}
}
@article{bin_high-speed_2011,
title = {A high-speed {BCI} based on code modulation {VEP}},
volume = {8},
issn = {1741-2552},
doi = {10.1088/1741-2560/8/2/025015},
abstract = {Recently, electroencephalogram-based brain-computer interfaces (BCIs) have attracted much attention in the fields of neural engineering and rehabilitation due to their noninvasiveness. However, the low communication speed of current BCI systems greatly limits their practical application. In this paper, we present a high-speed BCI based on code modulation of visual evoked potentials (c-VEP). Thirty-two target stimuli were modulated by a time-shifted binary pseudorandom sequence. A multichannel identification method based on canonical correlation analysis (CCA) was used for target identification. The online system achieved an average information transfer rate (ITR) of 108 ± 12 bits min(-1) on five subjects with a maximum ITR of 123 bits min(-1) for a single subject.},
language = {eng},
number = {2},
journal = {Journal of Neural Engineering},
author = {Bin, Guangyu and Gao, Xiaorong and Wang, Yijun and Li, Yun and Hong, Bo and Gao, Shangkai},
month = apr,
year = {2011},
pmid = {21436527},
keywords = {Algorithms, Brain Mapping, Electroencephalography, Evoked Potentials, Evoked Potentials, Visual, Humans, Photic Stimulation, Visual Cortex, Visual Perception},
pages = {025015}
}
@article{marinkovic_spatio-temporal_2014,
title = {Spatio-temporal dynamics and laterality effects of face inversion, feature presence and configuration, and face outline},
volume = {8},
issn = {1662-5161},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4226148/},
doi = {10.3389/fnhum.2014.00868},
abstract = {Although a crucial role of the fusiform gyrus (FG) in face processing has been demonstrated with a variety of methods, converging evidence suggests that face processing involves an interactive and overlapping processing cascade in distributed brain areas. Here we examine the spatio-temporal stages and their functional tuning to face inversion, presence and configuration of inner features, and face contour in healthy subjects during passive viewing. Anatomically-constrained magnetoencephalography (aMEG) combines high-density whole-head MEG recordings and distributed source modeling with high-resolution structural MRI. Each person's reconstructed cortical surface served to constrain noise-normalized minimum norm inverse source estimates. The earliest activity was estimated to the occipital cortex at {\textasciitilde}100 ms after stimulus onset and was sensitive to an initial coarse level visual analysis. Activity in the right-lateralized ventral temporal area (inclusive of the FG) peaked at {\textasciitilde}160 ms and was largest to inverted faces. Images containing facial features in the veridical and rearranged configuration irrespective of the facial outline elicited intermediate level activity. The M160 stage may provide structural representations necessary for downstream distributed areas to process identity and emotional expression. However, inverted faces additionally engaged the left ventral temporal area at {\textasciitilde}180 ms and were uniquely subserved by bilateral processing. This observation is consistent with the dual route model and spared processing of inverted faces in prosopagnosia. The subsequent deflection, peaking at {\textasciitilde}240 ms in the anterior temporal areas bilaterally, was largest to normal, upright faces. It may reflect initial engagement of the distributed network subserving individuation and familiarity. These results support dynamic models suggesting that processing of unfamiliar faces in the absence of a cognitive task is subserved by a distributed and interactive neural circuit.},
urldate = {2016-02-01},
journal = {Frontiers in Human Neuroscience},
author = {Marinkovic, Ksenija and Courtney, Maureen G. and Witzel, Thomas and Dale, Anders M. and Halgren, Eric},
month = nov,
year = {2014},
pmid = {25426044},
pmcid = {PMC4226148}
}
@article{amari_-divergence_2009,
title = {$\alpha$-{Divergence} {Is} {Unique}, {Belonging} to {Both} f-{Divergence} and {Bregman} {Divergence} {Classes}},
volume = {55},
issn = {0018-9448},
doi = {10.1109/TIT.2009.2030485},
number = {11},
journal = {Information Theory, IEEE Transactions on},
author = {Amari, S.-I.},
year = {2009},
keywords = {\$f\$-divergence, alpha-divergence, Bregman divergence, canonical divergence, dually flat structure, Entropy, f-divergence, Fisher information, Fisher metric, geometrical structure, geometry, Information geometry, information monotonicity, Kullback-Leibler divergence, Matrix decomposition, optimisation, optimization problems, Physics, positive arrays, Probability distribution, probability distributions, statistical distributions},
pages = {4925--4931}
}
@inproceedings{samek_robust_2013,
title = {Robust spatial filtering with beta divergence},
booktitle = {Advances in {Neural} {Information} {Processing} {Systems}},
author = {Samek, Wojciech and Blythe, Duncan and Müller, Klaus-Robert and Kawanabe, Motoaki},
year = {2013},
pages = {1007--1015}
}
@article{cincotti_comparison_2003,
title = {Comparison of different feature classifiers for brain computer interfaces},
journal = {Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on},
author = {Cincotti, F. and Scipione, A. and Timperi, A. and Mattia, D. and Marciani, A.G. and Millan, J. and Salinari, S. and Bianchi, L. and Bablioni, F.},
year = {2003},
pages = {645--647}
}
@article{dieleman_rotation-invariant_2015,
title = {Rotation-invariant convolutional neural networks for galaxy morphology prediction},
volume = {450},
number = {2},
journal = {Monthly Notices of the Royal Astronomical Society},
author = {Dieleman, Sander and Willett, Kyle W and Dambre, Joni},
year = {2015},
pages = {1441--1459}
}
@article{cartan_groupes_1929,
title = {Groupes simples clos et ouverts et géométrie riemannienne},
url = {https://eudml.org/doc/235727},
urldate = {2016-06-14},
journal = {Journal de mathématiques pures et appliquées},
author = {Cartan, Elie},
year = {1929},
pages = {1--34},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/2PX7BESW/235727.html:text/html}
}
@article{pfurtscheller_hybrid_2010,
title = {The hybrid {BCI}},
volume = {4},
journal = {Frontiers in neuroscience},
author = {Pfurtscheller, Gert and Allison, Brendan Z. and Brunner, Clemens and Bauernfeind, Gunther and Solis-Escalante, Teodoro and Scherer, Reinhold and Zander, Thorsten O. and Mueller-Putz, Gernot and Neuper, Christa and Birbaumer, Niels},
year = {2010}
}
@article{hochberg_reach_2012,
title = {Reach and grasp by people with tetraplegia using a neurally controlled robotic arm},
volume = {485},
copyright = {© 2012 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
issn = {0028-0836},
url = {http://www.nature.com/nature/journal/v485/n7398/abs/nature11076.html},
doi = {10.1038/nature11076},
abstract = {Paralysis following spinal cord injury, brainstem stroke, amyotrophic lateral sclerosis and other disorders can disconnect the brain from the body, eliminating the ability to perform volitional movements. A neural interface system could restore mobility and independence for people with paralysis by translating neuronal activity directly into control signals for assistive devices. We have previously shown that people with long-standing tetraplegia can use a neural interface system to move and click a computer cursor and to control physical devices. Able-bodied monkeys have used a neural interface system to control a robotic arm, but it is unknown whether people with profound upper extremity paralysis or limb loss could use cortical neuronal ensemble signals to direct useful arm actions. Here we demonstrate the ability of two people with long-standing tetraplegia to use neural interface system-based control of a robotic arm to perform three-dimensional reach and grasp movements. Participants controlled the arm and hand over a broad space without explicit training, using signals decoded from a small, local population of motor cortex (MI) neurons recorded from a 96-channel microelectrode array. One of the study participants, implanted with the sensor 5 years earlier, also used a robotic arm to drink coffee from a bottle. Although robotic reach and grasp actions were not as fast or accurate as those of an able-bodied person, our results demonstrate the feasibility for people with tetraplegia, years after injury to the central nervous system, to recreate useful multidimensional control of complex devices directly from a small sample of neural signals.},
language = {en},
number = {7398},
urldate = {2016-04-18},
journal = {Nature},
author = {Hochberg, Leigh R. and Bacher, Daniel and Jarosiewicz, Beata and Masse, Nicolas Y. and Simeral, John D. and Vogel, Joern and Haddadin, Sami and Liu, Jie and Cash, Sydney S. and van der Smagt, Patrick and Donoghue, John P.},
month = may,
year = {2012},
keywords = {Applied physics, Engineering, Medical research, Neuroscience, Technology},
pages = {372--375},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/46VC2IAZ/Hochberg et al. - 2012 - Reach and grasp by people with tetraplegia using a.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/SBH746MR/nature11076.html:text/html}
}
@inproceedings{wang_enhancing_2006,
title = {Enhancing {Evoked} {Responses} for {BCI} {Through} {Advanced} {ICA} {Techniques}},
booktitle = {Advances in {Medical}, {Signal} and {Information} {Processing} ({MEDSIP})},
author = {Wang, Suogang and James, Christopher J.},
year = {2006},
pages = {1--4}
}
@article{pan_enhancing_2011,
title = {Enhancing the classification accuracy of steady-state visual evoked potential-based brain-computer interfaces using phase constrained canonical correlation analysis},
volume = {8},
number = {3},
journal = {Journal of neural engineering},
author = {Pan, Jie and Gao, Xiaorong and Duan, Fang and Yan, Zheng and Gao, Shangkai},
year = {2011},
pages = {036027}
}
@article{brunner_current_2011,
title = {Current trends in hardware and software for brain-computer interfaces ({BCIs})},
volume = {8},
number = {2},
journal = {Journal of Neural Engineering},
author = {Brunner, P. and Bianchi, L. and Guger, C. and Cincotti, F. and Schalk, G.},
year = {2011},
pages = {025001}
}
@article{scherer_self-initiation_2007,
title = {Self-initiation of {EEG}-based brain-computer communication using the heart rate response},
volume = {4},
number = {4},
journal = {Journal of Neural Engineering},
author = {Scherer, R. and Müller-Putz, G. R. and Pfurtscheller, G.},
year = {2007},
pages = {L23}
}
@article{bayliss_single_1998,
title = {Single {Trial} {P}300 {Recognition} in a {Virtual} {Environment}},
journal = {University of Rochester},
author = {Bayliss, Jessica D. and Ballard, Dana H.},
year = {1998},
pages = {22--25}
}
@incollection{blankertz_berlin_2008,
series = {Lecture {Notes} in {Computer} {Science}},
title = {The {Berlin} {Brain}-{Computer} {Interface}},
volume = {5050},
abstract = {The Berlin Brain-Computer Interface (BBCI) uses a machine learning approach to extract subject-specific patterns from high-dimensional EEG-features optimized for revealing the user's mental state. Classical BCI application are brain actuated tools for patients such as prostheses (see Section 4.1) or mental text entry systems ([2] and see [3,4,5,6] for an overview on BCI). In these applications the BBCI uses natural motor competences of the users and specifically tailored pattern recognition algorithms for detecting the user's intent. But beyond rehabilitation, there is a wide range of possible applications in which BCI technology is used to monitor other mental states, often even covert ones (see also [7] in the fMRI realm). While this field is still largely unexplored, two examples from our studies are exemplified in Section 4.3 and 4.4.},
booktitle = {Computational {Intelligence}: {Research} {Frontiers}},
publisher = {Springer Berlin Heidelberg},
author = {Blankertz, Benjamin and Tangermann, Michael and Popescu, Florin and Krauledat, Matthias and Fazli, Siamac and Dónaczy, Márton and Curio, Gabriel and Müller, Klaus-Robert},
year = {2008},
pages = {79--101}
}
@article{dornhege_boosting_2004,
title = {Boosting bit rates in noninvasive {EEG} single-trial classifications by feature combination and multiclass paradigms},
volume = {51},
number = {6},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Dornhege, G. and Blankertz, B. and Curio, G. and Muller, K.-R.},
year = {2004},
pages = {993--1002}
}
@article{pires_statistical_2011,
title = {Statistical spatial filtering for a {P}300-based {BCI}: {Tests} in able-bodied, and patients with cerebral palsy and amyotrophic lateral sclerosis},
volume = {195},
number = {2},
journal = {Journal of Neuroscience Methods},
author = {Pires, Gabriel and Nunes, Urbano and Castelo-Branco, Miguel},
year = {2011},
pages = {270--281}
}
@incollection{zhu_online_2011,
series = {Lecture {Notes} in {Computer} {Science}},
title = {Online {BCI} {Implementation} of {High}-{Frequency} {Phase} {Modulated} {Visual} {Stimuli}},
volume = {6766},
booktitle = {Universal {Access} in {Human}-{Computer} {Interaction}. {Users} {Diversity}},
publisher = {Springer Berlin Heidelberg},
author = {Zhu, Danhua and Garcia-Molina, Gary and Mihajlović, Vojkan and Aarts, RonaldM},
editor = {Stephanidis, Constantine},
year = {2011},
pages = {645--654}
}
@article{schafer_shrinkage_2005,
title = {A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics},
volume = {4},
number = {1},
journal = {Statistical applications in genetics and molecular biology},
author = {Schäfer, Juliane and Strimmer, Korbinian},
year = {2005}
}
@article{_efficient_2008,
title = {An efficient {P}300-based brain-computer interface for disabled subjects},
volume = {167},
number = {1},
journal = {Journal of Neuroscience Methods},
year = {2008},
pages = {115--125}
}
@article{arsigny_geometric_2007,
title = {Geometric means in a novel vector space structure on symmetric positive-definite matrices},
volume = {29},
number = {1},
journal = {SIAM Journal on Matrix Analysis and Applications},
author = {Arsigny, Vincent and Fillard, Pierre and Pennec, Xavier and Ayache, Nicholas},
year = {2007},
pages = {328--347}
}
@article{kathner_portable_2013,
title = {A portable auditory {P}300 brain–computer interface with directional cues},
volume = {124},
issn = {1388-2457},
url = {http://www.sciencedirect.com/science/article/pii/S1388245712005640},
doi = {10.1016/j.clinph.2012.08.006},
abstract = {Objectives
The main objective of the current study was to implement and evaluate a P300 based brain–computer interface (BCI) speller that uses directional cues of auditory stimuli, which are presented over headphones. The interstimulus interval (ISI) was successively reduced to determine the optimal combination of speed and accuracy. The study further aimed at quantifying the differences in subjective workload between the auditory and the visual P300 spelling application. The influence of workload, mood and motivation on BCI performance and P300 amplitude was investigated.
Methods
Twenty healthy participants performed auditory and visual spelling tasks in an EEG experiment with online feedback.
Results
Sixteen of twenty participants performed at or above a level necessary for satisfactory communication (⩾70\% spelling accuracy) with the auditory BCI. Average bit rates of up to 2.76 bits/min (best subject 7.43 bits/min) were achieved. A significantly higher workload was reported for the auditory speller compared to the visual paradigm. Motivation significantly influenced P300 amplitude at Pz in the auditory condition.
Conclusions
The results of the online study suggest that the proposed paradigm offers a means of communication for most healthy users.
Significance
The described auditory BCI can serve as a communication channel for completely paralyzed patients.},
number = {2},
urldate = {2016-04-28},
journal = {Clinical Neurophysiology},
author = {Käthner, Ivo and Ruf, Carolin A. and Pasqualotto, Emanuele and Braun, Christoph and Birbaumer, Niels and Halder, Sebastian},
month = feb,
year = {2013},
keywords = {Auditory, Brain–computer interface, EEG, P300, Speller, Workload},
pages = {327--338},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/SFISPE88/Käthner et al. - 2013 - A portable auditory P300 brain–computer interface .pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ADWI3G4H/S1388245712005640.html:text/html}
}
@article{bamdadian_real_2011,
title = {Real coded {GA}-based {SVM} for motor imagery classification in a {Brain}-{Computer} {Interface}},
journal = {Control and Automation (ICCA), 2011 9th IEEE International Conference on},
author = {Bamdadian, A. and Guan, Cuntai and Ang, Kai Keng and Xu, Jianxin},
year = {2011},
pages = {1355--1359}
}
@article{kumar_design_2010,
title = {Design of {Support} {Vector} {Machines} with {Time} {Frequency} {Kernels} for classification of {EEG} signals},
journal = {Students' Technology Symposium (TechSym), 2010 IEEE},
author = {Kumar, A. and Mohanty, M.N. and Routray, A.},
year = {2010},
pages = {330--333}
}
@article{mcpartland_event-related_2004,
title = {Event-related brain potentials reveal anomalies in temporal processing of faces in autism spectrum disorder},
volume = {45},
url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1469-7610.2004.00318.x/full},
number = {7},
urldate = {2016-02-01},
journal = {Journal of Child Psychology and Psychiatry},
author = {McPartland, James and Dawson, Geraldine and Webb, Sara J. and Panagiotides, Heracles and Carver, Leslie J.},
year = {2004},
pages = {1235--1245},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/597RUX6P/McPartland et al. - 2004 - Event-related brain potentials reveal anomalies in.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/5VEN3K82/full.html:text/html}
}
@article{millan_noninvasive_2004,
title = {Noninvasive brain-actuated control of a mobile robot by human {EEG}},
volume = {51},
journal = {IEEE Transactions on Biomedical Engineering},
author = {Millan, Jose Del R. and Renkens, Frederic and Mourino, Josep and {Wulfram Gerstner}},
year = {2004},
pages = {1026--1033}
}
@article{bhattacharyya_performance_2010,
title = {Performance analysis of {LDA}, {QDA} and {KNN} algorithms in left-right limb movement classification from {EEG} data},
journal = {Systems in Medicine and Biology (ICSMB), 2010 International Conference on},
author = {Bhattacharyya, S. and Khasnobish, A. and Chatterjee, S. and Konar, A. and Tibarewala, D.N.},
year = {2010},
pages = {126--131}
}
@article{li_multi-class_2011,
title = {Multi-class imagery {EEG} recognition based on adaptive subject-based feature extraction and {SVM}-{BP} classifier},
journal = {Mechatronics and Automation (ICMA), 2011 International Conference on},
author = {Li, Mingai and Lin, Lin and Jia, Songmin},
year = {2011},
pages = {1184--1189}
}
@article{pfurtscheller_motor_2001,
title = {Motor imagery and direct brain-computer communication},
volume = {89},
number = {7},
journal = {Proceedings of the IEEE},
author = {Pfurtscheller, G. and Neuper, C.},
year = {2001},
pages = {1123--1134}
}
@book{fukunaga_introduction_1990,
title = {Introduction to statistical pattern recognition},
publisher = {Academic press},
author = {Fukunaga, Keinosuke},
year = {1990}
}
@article{birbaumer_brain-computer-interface_2006,
title = {Brain-computer-interface research: coming of age},
volume = {117},
issn = {1388-2457},
shorttitle = {Brain-computer-interface research},
doi = {10.1016/j.clinph.2005.11.002},
language = {eng},
number = {3},
journal = {Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology},
author = {Birbaumer, Niels},
month = mar,
year = {2006},
pmid = {16458595},
keywords = {Brain, Electroencephalography, Humans, Research, Research Design, User-Computer Interface},
pages = {479--483}
}
@article{renard_openvibe:_2010,
title = {{OpenViBE}: {An} {Open}-{Source} {Software} {Platform} to {Design}, {Test}, and {Use} {Brain}–{Computer} {Interfaces} in {Real} and {Virtual} {Environments}},
volume = {19},
abstract = {Abstract This paper describes the OpenViBE software platform which enables researchers to design, test, and use brain?computer interfaces (BCIs). BCIs are communication systems that enable users to send commands to computers solely by means of brain activity. BCIs are gaining interest among the virtual reality (VR) community since they have appeared as promising interaction devices for virtual environments (VEs). The key features of the platform are (1) high modularity, (2) embedded tools for visualization and feedback based on VR and 3D displays, (3) BCI design made available to non-programmers thanks to visual programming, and (4) various tools offered to the different types of users. The platform features are illustrated in this paper with two entertaining VR applications based on a BCI. In the first one, users can move a virtual ball by imagining hand movements, while in the second one, they can control a virtual spaceship using real or imagined foot movements. Online experiments with these applications together with the evaluation of the platform computational performances showed its suitability for the design of VR applications controlled with a BCI. OpenViBE is a free software distributed under an open-source license.},
number = {1},
journal = {Presence: Teleoperators and Virtual Environments},
author = {Renard, Yann and Lotte, Fabien and Gibert, Guillaume and Congedo, Marco and Maby, Emmanuel and Delannoy, Vincent and Bertrand, Olivier and Lécuyer, Anatole},
year = {2010},
pages = {35--53}
}
@misc{_online_????,
title = {Online {SSVEP}-based {BCI} using {Riemannian} geometry},
url = {http://www.sciencedirect.com/science/article/pii/S0925231216000540},
urldate = {2016-03-09},
file = {Online SSVEP-based BCI using Riemannian geometry:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/EJ5W3HKF/S0925231216000540.html:text/html}
}
@article{abdi_principal_2010,
title = {Principal component analysis},
volume = {2},
number = {4},
journal = {Wiley Interdisciplinary Reviews: Computational Statistics},
author = {Abdi, Hervé and Williams, Lynne J.},
year = {2010},
pages = {433--459}
}
@article{galan_brain-actuated_2008,
title = {A {Brain}-{Actuated} {Wheelchair}: {Asynchronous} and {Non}-{Invasive} {Brain}-{Computer} {Interfaces} for {Continuous} {Control} of {Robots}},
journal = {Clinical Neurophysiology},
author = {Galan, A. and Nuttin, M. and Lewand, E. and Ferrez, P. W. and Vanacker, G. and Philips, J. and Millan, J. Del R.},
year = {2008},
pages = {2159--69}
}
@incollection{hill_classifying_2006-1,
series = {Lecture {Notes} in {Computer} {Science}},
title = {Classifying {Event}-{Related} {Desynchronization} in {EEG}, {ECoG} and {MEG} {Signals}},
copyright = {©2006 Springer-Verlag Berlin Heidelberg},
isbn = {978-3-540-44412-1 978-3-540-44414-5},
url = {http://link.springer.com/chapter/10.1007/11861898_41},
abstract = {We employed three different brain signal recording methods to perform Brain-Computer Interface studies on untrained subjects. In all cases, we aim to develop a system that could be used for fast, reliable preliminary screening in clinical BCI application, and we are interested in knowing how long screening sessions need to be. Good performance could be achieved, on average, after the first 200 trials in EEG, 75–100 trials in MEG, or 25–50 trials in ECoG. We compare the performance of Independent Component Analysis and the Common Spatial Pattern algorithm in each of the three sensor types, finding that spatial filtering does not help in MEG, helps a little in ECoG, and improves performance a great deal in EEG. In all cases the unsupervised ICA algorithm performed at least as well as the supervised CSP algorithm, which can suffer from poor generalization performance due to overfitting, particularly in ECoG and MEG.},
language = {en},
number = {4174},
urldate = {2016-05-03},
booktitle = {Pattern {Recognition}},
publisher = {Springer Berlin Heidelberg},
author = {Hill, N. Jeremy and Lal, Thomas Navin and Schröder, Michael and Hinterberger, Thilo and Widman, Guido and Elger, Christian E. and Schölkopf, Bernhard and Birbaumer, Niels},
editor = {Franke, Katrin and Müller, Klaus-Robert and Nickolay, Bertram and Schäfer, Ralf},
month = sep,
year = {2006},
note = {DOI: 10.1007/11861898\_41},
keywords = {Algorithm Analysis and Problem Complexity, Artificial Intelligence (incl. Robotics), Computer Graphics, Image Processing and Computer Vision, Pattern Recognition},
pages = {404--413},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BMR2W9NS/Hill et al. - 2006 - Classifying Event-Related Desynchronization in EEG.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QCRU842C/10.html:text/html}
}
@inproceedings{baklouti_force_2008,
title = {Force controlled upper-limb powered exoskeleton for rehabilitation},
abstract = {The goal of this project is to develop an upper limb exoskeletal orthosis destinated to help disabled population to achieve arm movements. This orthosis is principally designed for people suffering from myopathy and muscle degeneration. Such patients cannot generate enough force to move alone their arm. This poster presents a new approach to control the exoskeleton using pressure sensors.},
booktitle = {Intelligent {Robots} and {Systems} ({IROS})},
author = {Baklouti, M. and Guyot, P. A. and Monacelli, E. and Couvet, S.},
year = {2008},
pages = {4202}
}
@article{falkenstein_erp_2000-1,
title = {{ERP} components on reaction errors and their functional significance: a tutorial},
volume = {51},
number = {23},
journal = {Biological Psychology},
author = {Falkenstein, Michael and Hoormann, Jorg and Christ, Stefan and {Joachim Hohnsbein}},
year = {2000},
pages = {87--107}
}
@misc{_emotiv_????,
title = {{EMOTIV} - {Brainwear}® {Wireless} {EEG} {Technology}},
url = {http://emotiv.com/},
abstract = {Wearables for the brain! The most credible, research grade mobile EEG systems on the market. Research, self assessment, cognitive performance.},
urldate = {2016-05-31},
journal = {Emotiv},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/GV6WHCGA/emotiv.com.html:text/html}
}
@article{vidaurre_towards_2010,
title = {Towards a cure for {BCI} illiteracy.},
volume = {23},
abstract = {Brain-Computer Interfaces (BCIs) allow a user to control a computer application by brain activity as acquired, e.g., by EEG. One of the biggest challenges in BCI research is to understand and solve the problem of {\textbackslash}"BCI Illiteracy{\textbackslash}", which is that BCI control does not work for a non-negligible portion of users (estimated 15 to 30\%). Here, we investigate the illiteracy problem in BCI systems which are based on the modulation of sensorimotor rhythms. In this paper, a sophisticated adaptation scheme is presented which guides the user from an initial subject-independent classifier that operates on simple features to a subject-optimized state-of-the-art classifier within one session while the user interacts the whole time with the same feedback application. While initial runs use supervised adaptation methods for robust co-adaptive learning of user and machine, final runs use unsupervised adaptation and therefore provide an unbiased measure of BCI performance. Using this approach, which does not involve any offline calibration measurement, good performance was obtained by good BCI participants (also one novice) after 3-6 min of adaptation. More importantly, the use of machine learning techniques allowed users who were unable to achieve successful feedback before to gain significant control over the BCI system. In particular, one participant had no peak of the sensory motor idle rhythm in the beginning of the experiment, but could develop such peak during the course of the session (and use voluntary modulation of its amplitude to control the feedback application).},
number = {2},
journal = {Brain Topography},
author = {Vidaurre, Carmen and Blankertz, Benjamin},
year = {2010},
pages = {194--198}
}
@article{zhang_asynchronous_2008,
title = {Asynchronous {P}300-{Based} {Brain}–{Computer} {Interfaces}: {A} {Computational} {Approach} {With} {Statistical} {Models}},
volume = {55},
number = {6},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Zhang, Haihong and Guan, Cuntai and Wang, Chuanchu},
year = {2008},
pages = {1754--1763}
}
@article{muller-putz_control_2008,
title = {Control of an {Electrical} {Prosthesis} {With} an {SSVEP}-{Based} {BCI}},
volume = {55},
number = {1},
journal = {IEEE Transactions on Biomedical Engineering},
author = {Muller-Putz, Gernot R. and Pfurtscheller, Gert},
year = {2008},
pages = {361--364}
}
@article{capilla_steady-state_2011,
title = {Steady-{State} {Visual} {Evoked} {Potentials} {Can} {Be} {Explained} by {Temporal} {Superposition} of {Transient} {Event}-{Related} {Responses}},
volume = {6},
number = {1},
journal = {PLoS ONE},
author = {Capilla, Almudena and Pazo-Alvarez, Paula and Darriba, Alvaro and Campo, Pablo and Gross, Joachim},
year = {2011},
pages = {e14543}
}
@article{pfurtscheller_existence_1997,
title = {On the existence of different types of central beta rhythms below 30 {Hz}},
volume = {102},
number = {4},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Pfurtscheller, G. and Stanck, A. and Edlinger, G.},
year = {1997},
pages = {316--325}
}
@book{huettel_functional_2004,
title = {Functional magnetic resonance imaging},
volume = {1},
url = {http://www.sinauer.com/media/wysiwyg/tocs/FMRI.pdf},
urldate = {2016-04-19},
publisher = {Sinauer Associates Sunderland},
author = {Huettel, Scott A. and Song, Allen W. and McCarthy, Gregory},
year = {2004},
file = {[PDF] from sinauer.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/5VWGWKEX/Huettel et al. - 2004 - Functional magnetic resonance imaging.pdf:application/pdf}
}
@article{kaufmann_face_2013,
title = {Face stimuli effectively prevent brain–computer interface inefficiency in patients with neurodegenerative disease},
volume = {124},
url = {http://www.sciencedirect.com/science/article/pii/S1388245712007353},
number = {5},
urldate = {2016-04-28},
journal = {Clinical Neurophysiology},
author = {Kaufmann, Tobias and Schulz, Stefan M. and Köblitz, Anja and Renner, Gregor and Wessig, Carsten and Kübler, Andrea},
year = {2013},
pages = {893--900},
file = {[HTML] from clinph-journal.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/BKVV9K3K/fulltext.html:text/html;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/HKP4KMES/S1388245712007353.html:text/html}
}
@article{yu_analysis_2014,
title = {Analysis the effect of {PCA} for feature reduction in non-stationary {EEG} based motor imagery of {BCI} system},
volume = {125},
url = {http://www.sciencedirect.com/science/article/pii/S0030402613012473},
number = {3},
urldate = {2016-05-11},
journal = {Optik-International Journal for Light and Electron Optics},
author = {Yu, Xinyang and Chum, Pharino and Sim, Kwee-Bo},
year = {2014},
pages = {1498--1502},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ZWSHT9HF/S0030402613012473.html:text/html}
}
@article{yan_classifying_2008,
title = {Classifying {EEG} {Signals} {Based} {HMM}-{AR}},
journal = {Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on},
author = {Yan, Tang and Jingtian, Tang and Andong, Gong and Wei, Wang},
year = {2008},
pages = {2111--2114}
}
@incollection{allison_could_2010,
series = {Human-{Computer} {Interaction} {Series}},
title = {Could {Anyone} {Use} a {BCI}?},
copyright = {©2010 Springer-Verlag London Limited},
isbn = {978-1-84996-271-1 978-1-84996-272-8},
url = {http://link.springer.com/chapter/10.1007/978-1-84996-272-8_3},
abstract = {Brain-computer interface (BCI) systems can provide communication and control for many users, but not all users. This problem exists across different BCI approaches; a “universal” BCI that works for everyone has never been developed. Instead, about 20\% of subjects are not proficient with a typical BCI system. Some groups have called this phenomenon “BCI illiteracy”. Some possible solutions have been explored, such as improved signal processing, training, and new tasks or instructions. These approaches have not resulted in a BCI that works for all users, probably because a small minority of users cannot produce detectable patterns of brain activity necessary to a particular BCI approach. We also discuss an underappreciated solution: switching to a different BCI approach. While the term “BCI illiteracy” elicits interesting comparisons between BCIs and natural languages, many issues are unclear. For example, comparisons across different studies have been problematic since different groups use different performance thresholds, and do not account for key factors such as the number of trials or size of the BCI’s alphabet. We also discuss challenges inherent in establishing widely used terms, definitions, and measurement approaches to facilitate discussions and comparisons among different groups.},
language = {en},
urldate = {2016-04-25},
booktitle = {Brain-{Computer} {Interfaces}},
publisher = {Springer London},
author = {Allison, Brendan Z. and Neuper, Christa},
editor = {Tan, Desney S. and Nijholt, Anton},
year = {2010},
note = {DOI: 10.1007/978-1-84996-272-8\_3},
keywords = {Computer Engineering, Computer Science, general, Information Systems and Communication Service, Input/Output and Data Communications, User Interfaces and Human Computer Interaction},
pages = {35--54},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/GTSS7VE5/978-1-84996-272-8_3.html:text/html}
}
@inproceedings{tomioka_logistic_2007,
title = {Logistic regression for single trial {EEG} classification},
volume = {19},
booktitle = {Advances in neural information processing systems ({NIPS})},
author = {Tomioka, Ryota and Aihara, Kazuyuki and Müller, Klaus-Robert},
year = {2007},
pages = {1377--1384}
}
@article{jia_frequency_2011,
title = {Frequency and {Phase} {Mixed} {Coding} in {SSVEP}-{Based} {Brain}–{Computer} {Interface}},
volume = {58},
number = {1},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Jia, Chuan and Gao, Xiaorong and Hong, Bo and Gao, Shangkai},
year = {2011},
pages = {200--206}
}
@article{herrmann_human_2001,
title = {Human {EEG} responses to 1-100 {Hz} flicker: resonance phenomena in visual cortex and their potential correlation to cognitive phenomena},
volume = {137},
issn = {0014-4819},
shorttitle = {Human {EEG} responses to 1-100 {Hz} flicker},
abstract = {The individual properties of visual objects, like form or color, are represented in different areas in our visual cortex. In order to perceive one coherent object, its features have to be bound together. This was found to be achieved in cat and monkey brains by temporal correlation of the firing rates of neurons which code the same object. This firing rate is predominantly observed in the gamma frequency range (approx. 30-80 Hz, mainly around 40 Hz). In addition, it has been shown in humans that stimuli which flicker at gamma frequencies are processed faster by our brains than when they flicker at different frequencies. These effects could be due to neural oscillators, which preferably oscillate at certain frequencies, so-called resonance frequencies. It is also known that neurons in visual cortex respond to flickering stimuli at the frequency of the flickering light. If neural oscillators exist with resonance frequencies, they should respond more strongly to stimulation with their resonance frequency. We performed an experiment, where ten human subjects were presented flickering light at frequencies from 1 to 100 Hz in 1-Hz steps. The event-related potentials exhibited steady-state oscillations at all frequencies up to at least 90 Hz. Interestingly, the steady-state potentials exhibited clear resonance phenomena around 10, 20, 40 and 80 Hz. This could be a potential neural basis for gamma oscillations in binding experiments. The pattern of results resembles that of multiunit activity and local field potentials in cat visual cortex.},
language = {eng},
number = {3-4},
journal = {Experimental Brain Research},
author = {Herrmann, C. S.},
month = apr,
year = {2001},
pmid = {11355381},
keywords = {Adult, Brain Mapping, Cognition, Electroencephalography, Evoked Potentials, Female, Humans, Male, Photic Stimulation, Visual Cortex},
pages = {346--353}
}
@article{lopez-gordo_high_2010,
title = {A high performance {SSVEP}-{BCI} without gazing},
journal = {Neural Networks (IJCNN), The 2010 International Joint Conference on},
author = {Lopez-Gordo, M.A. and Pelayo, F. and Prieto, A.},
year = {2010},
pages = {1--5}
}
@article{arjona_evaluation_2011,
title = {Evaluation of {LDA} {Ensembles} {Classifiers} for {Brain} {Computer} {Interface}},
journal = {Memorias del XVIII Congreso Argentino de Bioingeniería (SABI 2011)},
author = {Arjona, C. and Pentacolo, J. and Gareis, I. E. and Atum, Y. and Gentiletti, G. and Acevedo, R. C. and Rufiner, H. L.},
year = {2011}
}
@misc{_proceedings_????,
title = {Proceedings of the {Third} {International} {Workshop} on {Advances} in {Electrocorticography}},
url = {https://www-sciencedirect-com.etna.bib.uvsq.fr/science/article/pii/S1525505012005781},
urldate = {2016-04-15},
file = {Proceedings of the Third International Workshop on Advances in Electrocorticography:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/5KDJ4CHV/S1525505012005781.html:text/html}
}
@article{franaszczuk_application_1985,
title = {The application of parametric multichannel spectral estimates in the study of electrical brain activity},
volume = {51},
journal = {Biological Cybernetics},
author = {Franaszczuk, P. J. and Blinowska, K. J. and Kowalczyk, M.},
year = {1985},
pages = {239--247}
}
@article{movahedi_development_2013,
title = {Development of a {Brain} {Computer} {Interface} ({BCI}) {Speller} {System} {Based} on {SSVEP} {Signals}},
volume = {3},
number = {3 Sep},
journal = {Journal of Biomedical Physics and Engineering},
author = {Movahedi, MM and Mehdizadeh, AR and Alipour, A},
year = {2013}
}
@article{ritaccio_proceedings_2012,
title = {Proceedings of the {Third} {International} {Workshop} on {Advances} in {Electrocorticography}},
volume = {25},
url = {http://www.sciencedirect.com/science/article/pii/S1525505012005781},
number = {4},
urldate = {2016-04-18},
journal = {Epilepsy \& Behavior},
author = {Ritaccio, Anthony and Beauchamp, Michael and Bosman, Conrado and Brunner, Peter and Chang, Edward and Crone, Nathan and Gunduz, Aysegul and Gupta, Disha and Knight, Robert and Leuthardt, Eric and {others}},
year = {2012},
pages = {605--613},
file = {[HTML] from nih.gov:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/43ZX7W9F/PMC4041796.html:text/html;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/HMRF7F8R/S1525505012005781.html:text/html}
}
@article{looney_--ear_2012,
title = {The in-the-ear recording concept: {User}-centered and wearable brain monitoring},
volume = {3},
shorttitle = {The in-the-ear recording concept},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6378569},
number = {6},
urldate = {2016-05-30},
journal = {Pulse, IEEE},
author = {Looney, David and Kidmose, Preben and Park, Cheolsoo and Ungstrup, Michael and Rank, Mike Lind and Rosenkranz, Kari and Mandic, Danilo P.},
year = {2012},
pages = {32--42},
file = {[PDF] from ic.ac.uk:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/3T8XM9FT/Looney et al. - 2012 - The in-the-ear recording concept User-centered an.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/PEKWMDA7/login.html:text/html}
}
@article{millan_asynchronous_2009,
title = {Asynchronous non-invasive brain-actuated control of an intelligent wheelchair},
journal = {Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE},
author = {Millan, J.d.R. and Galan, F. and Vanhooydonck, D. and Lew, E. and Philips, J. and Nuttin, M.},
year = {2009},
pages = {3361--3364}
}
@inproceedings{zhang_classification_2015,
title = {Classification of {EEG} signals based on {AR} model and approximate entropy},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7280840},
urldate = {2016-05-12},
booktitle = {Neural {Networks} ({IJCNN}), 2015 {International} {Joint} {Conference} on},
publisher = {IEEE},
author = {Zhang, Yong and Ji, Xiaomin and Zhang, Yuting},
year = {2015},
pages = {1--6},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QR9A8C5N/login.html:text/html}
}
@article{guger_c._and_edlinger_g._and_harkam_w._and_niedermayer_i._and_pfurtscheller_g._how_2003,
title = {How many people are able to operate an {EEG}-based brain-computer interface ({BCI})?},
volume = {11},
number = {2},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {{Guger, C. and Edlinger, G. and Harkam, W. and Niedermayer, I. and Pfurtscheller, G.}},
year = {2003},
pages = {145--147}
}
@article{picton_p300_1992,
title = {The {P}300 {Wave} of the {Human} {Event}-{Related} {Potential}},
volume = {9},
number = {4},
journal = {Journal of Clinical Neurophysiology},
author = {Picton, Terence W.},
year = {1992},
pages = {456--479}
}
@article{mcfarland_spatial_1997,
title = {Spatial filter selection for {EEG}-based communication},
volume = {103},
number = {3},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {McFarland, Dennis J. and McCane, Lynn M. and David, Stephen V. and Wolpaw, Jonathan R.},
year = {1997},
pages = {386--394}
}
@article{lotte_exploring_2010,
title = {Exploring large virtual environments by thoughts using a brain-computer interface based on motor imagery and high-level commands},
volume = {19},
number = {1},
journal = {Presence: teleoperators and virtual environments},
author = {Lotte, Fabien and Van Langhenhove, Aurélien and Lamarche, Fabrice and Ernest, Thomas and Renard, Yann and Arnaldi, Bruno and Lécuyer, Anatole},
year = {2010},
pages = {54--70}
}
@inproceedings{xie_nonlinear_2013,
title = {On {A} {Nonlinear} {Generalization} of {Sparse} {Coding} and {Dictionary} {Learning}},
booktitle = {Proceedings of the 30th {International} {Conference} on {Machine} {Learning}},
publisher = {NIH Public Access},
author = {Xie, Yuchen and Ho, Jeffrey and Vemuri, Baba},
year = {2013},
pages = {1480}
}
@article{graves_novel_2009,
title = {A novel connectionist system for unconstrained handwriting recognition},
volume = {31},
number = {5},
journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on},
author = {Graves, Alex and Liwicki, Marcus and Fernández, Santiago and Bertolami, Roman and Bunke, Horst and Schmidhuber, Jürgen},
year = {2009},
pages = {855--868}
}
@article{boissonnat_natural_2001,
title = {Natural neighbor coordinates of points on a surface},
volume = {19},
issn = {0925-7721},
number = {2–3},
journal = {Computational Geometry},
author = {Boissonnat, Jean-Daniel and Cazals, Frédéric},
year = {2001},
note = {Combinatorial Curves and Surfaces},
pages = {155 -- 173}
}
@misc{_melomind_????,
title = {Melomind {\textbar}},
url = {http://melomind.com/fr/},
urldate = {2016-03-09},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ZWXMT9BU/fr.html:text/html}
}
@article{kim_rank-one_1975,
title = {Rank-{One} {Commutators} and {Hyperinvariant} {Subspaces}},
volume = {22},
number = {3},
journal = {Michigan Math. J.},
author = {Kim, H. W. and Pearcy, C. and Shields, A. L.},
year = {1975},
pages = {193--194}
}
@article{arsigny_log-euclidean_2006,
title = {Log-{Euclidean} metrics for fast and simple calculus on diffusion tensors},
volume = {56},
number = {2},
journal = {Magn. Reson. Med.},
author = {Arsigny, Vincent and Fillard, Pierre and Pennec, Xavier and Ayache, Nicholas},
year = {2006},
pages = {411--421}
}
@article{bayliss_single_2000,
title = {Single trial {P}3 epoch recognition in a virtual environment},
volume = {32-33},
journal = {Neurocomputing},
author = {Bayliss, Jessica D. and Ballard, Dana H.},
year = {2000},
pages = {637--642}
}
@article{donchin_surprise!_1981,
title = {Surprise!… {Surprise}?},
volume = {18},
issn = {1469-8986},
url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1469-8986.1981.tb01815.x/abstract},
doi = {10.1111/j.1469-8986.1981.tb01815.x},
abstract = {The nature of the psychophysiological enterprise is examined as it bears on the study of the endogenous components of event-related brain potentials (ERP). The view is taken that success in Psychophysiology should be measured by the degree to which psychophysiological data can be used in elucidating the processes that underly the behavioral product rather than by the enumeration of psychophysiological “correlates” of behavior. It is proposed that endogenous ERP components are best viewed as manifestations of the activities of “subroutines” invoked during the informational transactions of the brain. A theoretical account of an ERP component consists of the specification of the functional role of the subroutine it manifests. Studies of the P300 components are examined for the contribution they make to the development of such a theory of the P300. Experiments focusing on P300 latency and amplitude are reviewed and it is concluded that P300 may be a manifestation of the processes whereby schemas are revised. The relationship between P300 and the Orienting Reflex is discussed within the framework of this model. It is suggested that P300 amplitude may predict the memorability of events. A preliminary test of this prediction is described.},
language = {en},
number = {5},
urldate = {2016-05-02},
journal = {Psychophysiology},
author = {Donchin, Emanuel},
month = sep,
year = {1981},
keywords = {Cognitive task performance, Event-related brain potentials, Memorability of events, Orienting reflex, P300, Stimulus probability},
pages = {493--513},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QRV967NH/Donchin - 1981 - Surprise!… Surprise.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/M57JX2VI/abstract.html:text/html}
}
@article{rivet*_xdawn_2009,
title = {{xDAWN} {Algorithm} to {Enhance} {Evoked} {Potentials}: {Application} to {Brain} \#x2013;{Computer} {Interface}},
volume = {56},
issn = {0018-9294},
shorttitle = {{xDAWN} {Algorithm} to {Enhance} {Evoked} {Potentials}},
doi = {10.1109/TBME.2009.2012869},
abstract = {A brain-computer interface (BCI) is a communication system that allows to control a computer or any other device thanks to the brain activity. The BCI described in this paper is based on the P300 speller BCI paradigm introduced by Farwell and Donchin. An unsupervised algorithm is proposed to enhance P300 evoked potentials by estimating spatial filters; the raw EEG signals are then projected into the estimated signal subspace. Data recorded on three subjects were used to evaluate the proposed method. The results, which are presented using a Bayesian linear discriminant analysis classifier, show that the proposed method is efficient and accurate.},
number = {8},
journal = {IEEE Transactions on Biomedical Engineering},
author = {Rivet*, B. and Souloumiac, A. and Attina, V. and Gibert, G.},
month = aug,
year = {2009},
keywords = {Adult, Algorithms, Application software, Artificial Intelligence, Bayesian linear discriminant analysis classifier, Bayesian methods, Bayes methods, bioelectric potentials, Brain, brain activity, brain-computer interface, Brain–computer interface (BCI), brain-computer interfaces, brain computer interfaces, Communication system control, Computer interfaces, Control systems, EEG signal, Electroencephalography, evoked potential, Evoked Potentials, Humans, Laboratories, Linear discriminant analysis, Male, Man-Machine Systems, medical disorders, medical signal processing, neuromuscular disorder, P300 speller, P300 speller BCI paradigm, signal classification, Signal Processing, Computer-Assisted, spatial enhancement, spatial filter, spatial filters, Stochastic processes, unsupervised algorithm, unsupervised learning, xDAWN algorithm},
pages = {2035--2043},
file = {IEEE Xplore Abstract Record:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/N9N9I48S/login.html:text/html}
}
@article{ishita_development_2007,
title = {Development of {P}300 {Detection} {Algorithm} for {Brain} {Computer} {Interface} in {Single} {Trial}},
journal = {Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference on},
author = {Ishita, H. and Sakai, M. and Watanabe, J. and Chen, Wenxi and {Darning Wei}},
year = {2007},
pages = {1100--1105}
}
@article{pfurtscheller_event-related_1994,
title = {Event-related synchronization of mu rhythm in the {EEG} over the cortical hand area in man},
volume = {174},
number = {1},
journal = {Neuroscience Letters},
author = {Pfurtscheller, Gert and Neuper, Christa},
year = {1994},
pages = {93--96}
}
@article{wang_motor_2011,
title = {Motor {Imagery} {BCI} {Research} {Based} on {Hilbert}-{Huang} {Transform} and {Genetic} {Algorithm}},
journal = {Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on},
author = {Wang, Lei and Xu, Guizhi and Wang, Jiang and Yang, Shuo and Yan, Weili},
year = {2011},
pages = {1--4}
}
@article{cheng_design_2002,
title = {Design and implementation of a brain-computer interface with high transfer rates},
volume = {49},
number = {10},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Cheng, Ming and Gao, Xiaorong and Gao, Shangkai and Xu, Dingfeng},
year = {2002},
pages = {1181--1186}
}
@article{lin_frequency_2006,
title = {Frequency {Recognition} {Based} on {Canonical} {Correlation} {Analysis} for {SSVEP}-{Based} {BCIs}},
volume = {53},
number = {12},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Lin, Zhonglin and Zhang, Changshui and Wu, Wei and Gao, Xiaorong},
year = {2006},
pages = {2610--2614}
}
@article{proverbio_electromagnetic_2003,
title = {Electromagnetic manifestations of mind and brain},
volume = {2},
journal = {The cognitive electrophysiology of mind and brain},
author = {Proverbio, A. M. and Zani, A.},
year = {2003},
pages = {13--37}
}
@article{taylor_direct_2002,
title = {Direct {Cortical} {Control} of 3D {Neuroprosthetic} {Devices}},
volume = {296},
issn = {0036-8075, 1095-9203},
url = {http://science.sciencemag.org/content/296/5574/1829},
doi = {10.1126/science.1070291},
abstract = {Three-dimensional (3D) movement of neuroprosthetic devices can be controlled by the activity of cortical neurons when appropriate algorithms are used to decode intended movement in real time. Previous studies assumed that neurons maintain fixed tuning properties, and the studies used subjects who were unaware of the movements predicted by their recorded units. In this study, subjects had real-time visual feedback of their brain-controlled trajectories. Cell tuning properties changed when used for brain-controlled movements. By using control algorithms that track these changes, subjects made long sequences of 3D movements using far fewer cortical units than expected. Daily practice improved movement accuracy and the directional tuning of these units.},
language = {en},
number = {5574},
urldate = {2016-04-18},
journal = {Science},
author = {Taylor, Dawn M. and Tillery, Stephen I. Helms and Schwartz, Andrew B.},
month = jun,
year = {2002},
pmid = {12052948},
pages = {1829--1832},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/HKUEW4M9/1829.html:text/html}
}
@article{barachant_multiclass_2012,
title = {Multiclass brain–computer interface classification by {Riemannian} geometry},
volume = {59},
number = {4},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Barachant, Alexandre and Bonnet, Stéphane and Congedo, Marco and Jutten, Christian},
year = {2012},
pages = {920--928}
}
@article{manoochehri_new_2011,
title = {The new post processing method for self-paced {BCI} system},
journal = {Biomedical Engineering (ICBME), 2011 18th Iranian Conference of},
author = {Manoochehri, M. and Moradi, M.H.},
year = {2011},
pages = {152--155}
}
@article{muller-putz_towards_2015,
title = {Towards noninvasive hybrid brain–computer interfaces: framework, practice, clinical application, and beyond},
volume = {103},
shorttitle = {Towards noninvasive hybrid brain–computer interfaces},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7109824},
number = {6},
urldate = {2016-05-31},
journal = {Proceedings of the IEEE},
author = {Muller-Putz, Gernot and Leeb, Robert and Tangermann, Michael and Hohne, Johannes and Kubler, Andrea and Cincotti, Febo and Mattia, Donatella and Rupp, Rudiger and Muller, Klaus-Robert and Millan, Del R. and {others}},
year = {2015},
pages = {926--943},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/MAEMVG62/abs_all.html:text/html}
}
@article{van_erp_brain-computer_2012,
title = {Brain-computer interfaces: beyond medical applications},
shorttitle = {Brain-computer interfaces},
url = {http://www.computer.org/csdl/mags/co/2012/04/mco2012040026.html},
number = {4},
urldate = {2016-05-30},
journal = {Computer},
author = {Van Erp, Jan BF and Lotte, Fabien and Tangermann, Michael},
year = {2012},
pages = {26--34},
file = {[PDF] from archives-ouvertes.fr:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ZFMX23AR/Van Erp et al. - 2012 - Brain-computer interfaces beyond medical applicat.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/MJQCSVTC/mco2012040026.html:text/html}
}
@article{jeunet_why_2016,
title = {Why {Standard} {Brain}-{Computer} {Interface} ({BCI}) {Training} {Protocols} {Should} be {Changed}: {An} {Experimental} {Study}},
shorttitle = {Why {Standard} {Brain}-{Computer} {Interface} ({BCI}) {Training} {Protocols} {Should} be {Changed}},
url = {https://hal.inria.fr/hal-01302154/},
urldate = {2016-04-25},
journal = {Journal of Neural Engineering},
author = {Jeunet, Camille and Jahanpour, Emilie and Lotte, Fabien},
year = {2016},
file = {[PDF] from inria.fr:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ANH2D9ZA/Jeunet et al. - 2016 - Why Standard Brain-Computer Interface (BCI) Traini.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/HB4WR9P5/hal-01302154.html:text/html}
}
@article{chebbi_means_2012,
title = {Means of {Hermitian} positive-definite matrices based on the log-determinant $\alpha$-divergence function},
volume = {436},
number = {7},
journal = {Linear Algebra and its Applications},
author = {Chebbi, Zeineb and Moakher, Maher},
year = {2012},
pages = {1872--1889}
}
@article{neuper_enhancement_1999,
title = {Enhancement of left-right sensorimotor {EEG} differences during feedback-regulated motor imagery},
volume = {16},
number = {4},
journal = {Clinical Neurology},
author = {Neuper, C. and Pfurtscheller, G. and Schlogl, A.},
year = {1999},
pages = {373--382}
}
@article{rellecke_emotion_2013,
title = {Emotion {Effects} on the {N}170: {A} {Question} of {Reference}?},
volume = {26},
issn = {0896-0267, 1573-6792},
shorttitle = {Emotion {Effects} on the {N}170},
url = {http://link.springer.com/10.1007/s10548-012-0261-y},
doi = {10.1007/s10548-012-0261-y},
language = {en},
number = {1},
urldate = {2016-02-01},
journal = {Brain Topography},
author = {Rellecke, Julian and Sommer, Werner and Schacht, Annekathrin},
month = jan,
year = {2013},
pages = {62--71},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QV4TMKTS/Rellecke et al. - 2013 - Emotion effects on the N170 a question of referen.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/XCV88VNJ/s10548-012-0261-y.html:text/html}
}
@book{jost_riemannian_2011,
title = {Riemannian geometry and geometric analysis},
volume = {62011},
publisher = {Springer},
author = {Jost, Jürgen},
year = {2011}
}
@article{allison_toward_2010,
title = {Toward a hybrid brain computer interface based on imagined movement and visual attention},
volume = {7},
number = {2},
journal = {Journal of Neural Engineering},
author = {Allison, B. Z. and Brunner, C. and Kaiser, V. and Muller-Putz, G. R. and {C Neuper} and Pfurtscheller, G.},
year = {2010},
pages = {026007}
}
@article{zhu_survey_2010,
title = {A survey of stimulation methods used in {SSVEP}-based {BCIs}},
volume = {2010},
issn = {1687-5265},
journal = {Intell. Neuroscience},
author = {Zhu, Danhua and Bieger, Jordi and Molina, Gary Garcia and Aarts, Ronald M.},
year = {2010},
pages = {1--12}
}
@article{legeny_toward_2013,
title = {Toward {Contextual} {SSVEP}-{Based} {BCI} {Controller}: {Smart} {Activation} of {Stimuli} and {Control} {Weighting}},
volume = {5},
number = {2},
journal = {Computational Intelligence and AI in Games, IEEE Transactions on},
author = {Legeny, J. and Viciana-Abad, R. and Lécuyer, A.},
month = jun,
year = {2013},
pages = {111--116}
}
@article{zhang_bci_2012,
title = {{BCI} {Competition} {IV} – {Data} {Set} {I}: {Learning} {Discriminative} {Patterns} for {Self}-{Paced} {EEG}-{Based} {Motor} {Imagery} {Detection}},
volume = {6},
issn = {1662-4548},
shorttitle = {{BCI} {Competition} {IV} – {Data} {Set} {I}},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3272647/},
doi = {10.3389/fnins.2012.00007},
abstract = {Detecting motor imagery activities versus non-control in brain signals is the basis of self-paced brain-computer interfaces (BCIs), but also poses a considerable challenge to signal processing due to the complex and non-stationary characteristics of motor imagery as well as non-control. This paper presents a self-paced BCI based on a robust learning mechanism that extracts and selects spatio-spectral features for differentiating multiple EEG classes. It also employs a non-linear regression and post-processing technique for predicting the time-series of class labels from the spatio-spectral features. The method was validated in the BCI Competition IV on Dataset I where it produced the lowest prediction error of class labels continuously. This report also presents and discusses analysis of the method using the competition data set.},
urldate = {2016-04-25},
journal = {Frontiers in Neuroscience},
author = {Zhang, Haihong and Guan, Cuntai and Ang, Kai Keng and Wang, Chuanchu},
month = feb,
year = {2012},
pmid = {22347153},
pmcid = {PMC3272647},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/IG6EXISU/Zhang et al. - 2012 - BCI Competition IV – Data Set I Learning Discrimi.pdf:application/pdf}
}
@article{millan_combining_2010,
title = {Combining {Brain}-{Computer} {Interfaces} and {Assistive} {Technologies}: {State}-of-the-{Art} and {Challenges}},
volume = {4},
number = {161},
journal = {Frontiers in Neuroscience},
author = {Millán, José del R. and Rupp, Rudiger and Mueller-Putz, Gernot and Murray-Smith, Roderick and Giugliemma, Claudio and Tangermann, Michael and Vidaurre, Carmen and Cincotti, Febo and Kubler, Andrea and Leeb, Robert and Neuper, Christa and Mueller, Klaus R and Mattia, Donatella},
year = {2010}
}
@article{ozmen_discrimination_2011,
title = {Discrimination between mental and motor tasks of {EEG} signals using different classification methods},
journal = {Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on},
author = {Ozmen, N.G. and Ktu, L.G.},
year = {2011},
pages = {143--147}
}
@article{gervain_near-infrared_2011,
title = {Near-infrared spectroscopy: {A} report from the {McDonnell} infant methodology consortium},
volume = {1},
issn = {1878-9293},
shorttitle = {Near-infrared spectroscopy},
url = {http://www.sciencedirect.com/science/article/pii/S1878929310000058},
doi = {10.1016/j.dcn.2010.07.004},
abstract = {Near-infrared spectroscopy (NIRS) is a new and increasingly widespread brain imaging technique, particularly suitable for young infants. The laboratories of the McDonnell Consortium have contributed to the technological development and research applications of this technique for nearly a decade. The present paper provides a general introduction to the technique as well as a detailed report of the methodological innovations developed by the Consortium. The basic principles of NIRS and some of the existing developmental studies are reviewed. Issues concerning technological improvements, parameter optimization, possible experimental designs and data analysis techniques are discussed and illustrated by novel empirical data.},
number = {1},
urldate = {2016-04-19},
journal = {Developmental Cognitive Neuroscience},
author = {Gervain, Judit and Mehler, Jacques and Werker, Janet F. and Nelson, Charles A. and Csibra, Gergely and Lloyd-Fox, Sarah and Shukla, Mohinish and Aslin, Richard N.},
month = jan,
year = {2011},
keywords = {Infants, Near-infrared spectroscopy, Newborns, Optical imaging},
pages = {22--46},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/WB8NZVFE/Gervain et al. - 2011 - Near-infrared spectroscopy A report from the McDo.pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/Z8AFF7DJ/S1878929310000058.html:text/html}
}
@article{panicker_adaptation_2010,
title = {Adaptation in {P}300 brain–computer interfaces: {A} two-classifier cotraining approach},
volume = {57},
number = {12},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Panicker, Rajesh C and Puthusserypady, Sadasivan and Sun, Ying},
year = {2010},
pages = {2927--2935}
}
@article{foley_considerations_1972,
title = {Considerations of sample and feature size},
volume = {18},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1054863},
number = {5},
urldate = {2016-05-29},
journal = {Information Theory, IEEE Transactions on},
author = {Foley, Donald H.},
year = {1972},
pages = {618--626},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/2HMAPBSB/login.html:text/html}
}
@incollection{rocon_introduction:_2011,
title = {Introduction: {Exoskeletons} in {Rehabilitation} {Robotics}},
volume = {69},
abstract = {Rehabilitation Robotics has been defined as the combination of industrial robotics and medical rehabilitation, thus encompassing many areas, including mechanical and electrical engineering, biomedical engineering, artificial intelligence and sensor and actuator technology. Medical rehabilitation often refers to the process by which human function, be it physical or cognitive, is restored at least partially to their "normal" condition.},
booktitle = {Springer {Tracts} in {Advanced} {Robotics}},
author = {Rocon, E. and Pons, J.},
year = {2011},
pages = {1--20}
}
@article{finke_hybrid_2011,
title = {A hybrid brain interface for a humanoid robot assistant},
journal = {Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE},
author = {Finke, A. and Knoblauch, A. and Koesling, H. and Ritter, H.},
year = {2011},
pages = {7421--7424}
}
@article{zhang_novel_2012,
title = {A novel {BCI} based on {ERP} components sensitive to configural processing of human faces},
volume = {9},
issn = {1741-2552},
url = {http://stacks.iop.org/1741-2552/9/i=2/a=026018},
doi = {10.1088/1741-2560/9/2/026018},
abstract = {This study introduces a novel brain–computer interface (BCI) based on an oddball paradigm using stimuli of facial images with loss of configural face information (e.g., inversion of face). To the best of our knowledge, till now the configural processing of human faces has not been applied to BCI but widely studied in cognitive neuroscience research. Our experiments confirm that the face-sensitive event-related potential (ERP) components N170 and vertex positive potential (VPP) have reflected early structural encoding of faces and can be modulated by the configural processing of faces. With the proposed novel paradigm, we investigate the effects of ERP components N170, VPP and P300 on target detection for BCI. An eight-class BCI platform is developed to analyze ERPs and evaluate the target detection performance using linear discriminant analysis without complicated feature extraction processing. The online classification accuracy of 88.7\% and information transfer rate of 38.7 bits min −1 using stimuli of inverted faces with only single trial suggest that the proposed paradigm based on the configural processing of faces is very promising for visual stimuli-driven BCI applications.},
language = {en},
number = {2},
urldate = {2016-04-28},
journal = {Journal of Neural Engineering},
author = {Zhang, Yu and Zhao, Qibin and Jin, Jing and Wang, Xingyu and Cichocki, Andrzej},
year = {2012},
pages = {026018},
file = {IOP Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/JNMAEH2I/Zhang et al. - 2012 - A novel BCI based on ERP components sensitive to c.pdf:application/pdf}
}
@article{pfurtscheller_brain-computer_1993,
title = {Brain-{Computer} {Interface} - a new communication device for handicapped persons},
volume = {16},
abstract = {A Brain-Computer Interface (BCI) is a system which can bypass the normal motor output through the spine by using bioelectrical signals recorded on the intact scalp during purely mental activity. Such a BCI must be able to classify EEG patterns on-line and can be used to control, e.g. the movement of a cursor on a monitor. First results on a BCI developed in Graz are reported: 85\% correct movements can be obtained after only a few days training.},
number = {3},
journal = {Journal of Microcomputer Applications},
author = {Pfurtscheller, Gert and Flotzinger, Doris and Kalcher, Joachim},
month = jul,
year = {1993},
pages = {293--299}
}
@article{szuromi_p300_2010,
title = {P300 deficits in adults with attention deficit hyperactivity disorder: a meta-analysis},
volume = {41},
number = {7},
journal = {Psychol Med.},
author = {Szuromi, B. and Czobor, P. and Komlosi, S. and Bitter, I.},
year = {2010},
pages = {1529--1538}
}
@article{cecotti_self-paced_2010,
title = {A {Self}-{Paced} and {Calibration}-{Less} {SSVEP}-{Based} {Brain} {Computer} {Interface} {Speller}},
volume = {18},
number = {2},
journal = {Neural Systems and Rehabilitation Engineering, IEEE Transactions on},
author = {Cecotti, H.},
year = {2010},
pages = {127--133}
}
@incollection{fletcher_principal_2004,
series = {{LNCS}},
title = {Principal {Geodesic} {Analysis} on {Symmetric} {Spaces}: {Statistics} of {Diffusion} {Tensors}},
volume = {3117},
booktitle = {Computer {Vision} and {Mathematical} {Methods} in {Medical} and {Biomedical} {Image} {Analysis}},
publisher = {Springer},
author = {{Fletcher} and Joshi, Sarang},
year = {2004},
pages = {87--98}
}
@article{barachant_plug&play_2014,
title = {A {Plug}\&{Play} {P}300 {BCI} {Using} {Information} {Geometry}},
url = {http://arxiv.org/abs/1409.0107},
urldate = {2016-06-01},
journal = {arXiv preprint arXiv:1409.0107},
author = {Barachant, Alexandre and Congedo, Marco},
year = {2014},
file = {[PDF] from arxiv.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/CBD3I477/Barachant and Congedo - 2014 - A Plug&Play P300 BCI Using Information Geometry.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/KNHZBNGE/1409.html:text/html}
}
@article{sellers_p300-based_2006,
title = {A {P}300-based brain-computer interface: {Initial} tests by {ALS} patients},
volume = {117},
number = {3},
journal = {Clinical Neurophysiology},
author = {Sellers, Eric W. and Donchin, Emanuel},
year = {2006},
pages = {538--548}
}
@article{musallam_cognitive_2004,
title = {Cognitive {Control} {Signals} for {Neural} {Prosthetics}},
volume = {305},
copyright = {American Association for the Advancement of Science},
issn = {0036-8075, 1095-9203},
url = {http://science.sciencemag.org/content/305/5681/258},
doi = {10.1126/science.1097938},
abstract = {Recent development of neural prosthetics for assisting paralyzed patients has focused on decoding intended hand trajectories from motor cortical neurons and using this signal to control external devices. In this study, higher level signals related to the goals of movements were decoded from three monkeys and used to position cursors on a computer screen without the animals emitting any behavior. Their performance in this task improved over a period of weeks. Expected value signals related to fluid preference, the expected magnitude, or probability of reward were decoded simultaneously with the intended goal. For neural prosthetic applications, the goal signals can be used to operate computers, robots, and vehicles, whereas the expected value signals can be used to continuously monitor a paralyzed patient's preferences and motivation.
In monkeys, the activity of neurons used for planning tasks can direct an artificial limb to move to a goal.
In monkeys, the activity of neurons used for planning tasks can direct an artificial limb to move to a goal.},
language = {en},
number = {5681},
urldate = {2016-04-18},
journal = {Science},
author = {Musallam, S. and Corneil, B. D. and Greger, B. and Scherberger, H. and Andersen, R. A.},
month = jul,
year = {2004},
pmid = {15247483},
pages = {258--262},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/RS5VAZJ6/258.html:text/html}
}
@article{schettini_self-calibration_2014,
title = {Self-calibration algorithm in an asynchronous {P}300-based brain–computer interface},
volume = {11},
number = {3},
journal = {Journal of neural engineering},
author = {Schettini, F and Aloise, F and Aricò, P and Salinari, S and Mattia, D and Cincotti, F},
year = {2014},
pages = {035004}
}
@article{farwell_talking_1988,
title = {Talking off the top of your head: {Toward} a mental prosthesis utilizing event-related brain potentials},
volume = {70},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Farwell, L. A. and Donchin, E.},
year = {1988},
pages = {510--523}
}
@inproceedings{kalunga_hybrid_2014,
title = {Hybrid interface: {Integrating} {BCI} in multimodal human-machine interfaces},
shorttitle = {Hybrid interface},
doi = {10.1109/AIM.2014.6878132},
abstract = {In the context of assistive technologies, it is important to design systems that adapt to the user specificities, and to rely as much as possible on the residual capacities of each user. We define a new methodology in the context of assistive robotics: it is an hybrid approach where a physical interface is complemented by a Brain-Computer Interface (BCI). An implementation of such methodology is proposed, using a 3D touchless interface for continuous control and a steady-state visually evoked potential (SSVEP)-based BCI for triggering specific actions. We describe a novel algorithm for classification of SSVEP signals based on Canonical Correlation Analysis (CCA) and Support Vector Machines (SVM). Its reliability and robustness are assessed in an online setup and its results are compared to existing algorithms. Finally, an experimental evaluation of the proposed system is performed with a 3D navigation task in a Virtual Environment (VE). The system is also embedded on an assistive robotic arm exoskeleton to validate its feasibility.},
booktitle = {2014 {IEEE}/{ASME} {International} {Conference} on {Advanced} {Intelligent} {Mechatronics} ({AIM})},
author = {Kalunga, E. K. and Chevallier, S. and Rabreau, O. and Monacelli, E.},
month = jul,
year = {2014},
keywords = {3D navigation task, 3D touchless interface, Accuracy, assistive robotic arm exoskeleton, assistive technologies, BCI, bcihybrid, brain-computer interface, brain-computer interfaces, bvi, canonical correlation analysis, CCA, continuous control, Control systems, Electroencephalography, ethicomp2015, Exoskeletons, human computer interaction, hybrid interface, multimodal human-machine interfaces, SSVEP signals, steady-state visually evoked potential, Support vector machines, SVM, Three-dimensional displays, VE, virtual environment, Virtual environments, visual evoked potentials},
pages = {530--535},
file = {IEEE Xplore Abstract Record:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/6HIETH2B/login.html:text/html}
}
@article{fletcher_principal_2004-1,
title = {Principal geodesic analysis for the study of nonlinear statistics of shape},
volume = {23},
number = {8},
journal = {Medical Imaging, IEEE Transactions on},
author = {Fletcher, P Thomas and Lu, Conglin and Pizer, Stephen M and Joshi, Sarang},
year = {2004},
pages = {995--1005}
}
@article{pfurtscheller_graphical_1977,
title = {Graphical display and statistical evaluation of event-related desynchronization ({ERD})},
volume = {43},
number = {5},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Pfurtscheller, Gert},
year = {1977},
pages = {757--760}
}
@article{lotte_electroencephalography_2015,
title = {Electroencephalography ({EEG})-{Based} {Brain}–{Computer} {Interfaces}},
url = {http://onlinelibrary.wiley.com/doi/10.1002/047134608X.W8278/full},
urldate = {2016-05-30},
journal = {Wiley Encyclopedia of Electrical and Electronics Engineering},
author = {Lotte, Fabien and Bougrain, Laurent and Clerc, Maureen},
year = {2015},
file = {[PDF] from inria.fr:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/GZMZGC8F/Lotte et al. - 2015 - Electroencephalography (EEG)-Based Brain–Computer .pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/S7KNMR2Z/full.html:text/html}
}
@article{del_r_millan_local_2002,
title = {A local neural classifier for the recognition of {EEG} patterns associated to mental tasks},
volume = {13},
number = {3},
journal = {Neural Networks, IEEE Transactions on},
author = {del R Millan, J. and Mourino, J. and Franze, M. and Cincotti, F. and Varsta, M. and Heikkonen, J. and Babiloni, F.},
year = {2002},
pages = {678--686}
}
@article{guger_real-time_2000,
title = {Real-time {EEG} analysis with subject-specific spatial patterns for a brain-computer interface ({BCI})},
volume = {8},
number = {4},
journal = {Rehabilitation Engineering, IEEE Transactions on},
author = {Guger, C. and Ramoser, H. and Pfurtscheller, G.},
year = {2000},
pages = {447--456}
}
@article{dingyin_feature_2011,
title = {Feature extraction of motor imagery {EEG} signals based on wavelet packet decomposition},
journal = {Complex Medical Engineering (CME), 2011 IEEE/ICME International Conference on},
author = {Dingyin, Hu and Wei, Li and Xi, Chen},
year = {2011},
pages = {694--697}
}
@inproceedings{spuler_one_2012,
title = {One class {SVM} and {Canonical} {Correlation} {Analysis} increase performance in a c-{VEP} based {Brain}-{Computer} {Interface} ({BCI})},
volume = {4},
booktitle = {Proceedings of 20th {European} {Symposium} on {Artificial} {Neural} {Networks} ({ESANN} 2012), {Bruges}, {Belgium}},
author = {Spüler, Martin and Rosenstiel, Wolfgang and Bogdan, Martin},
year = {2012},
pages = {103--108}
}
@book{gazzaniga_cognitive_2013,
edition = {4th edition},
title = {Cognitive {Neuroscience}: {The} {Biology} of the {Mind}, 4th {Edition}},
isbn = {978-0-393-91348-4},
shorttitle = {Cognitive {Neuroscience}},
abstract = {The most authoritative cognitive neuroscience text is also the most accessible. The first textbook for the course, and still the market leader, Cognitive Neuroscience has been thoroughly refreshed, rethought, and reorganized to enhance students’ and instructors’ experience. A stunning, all new art program conveys data and concepts clearly, and new chapter-opening Anatomical Orientation figures help students get their bearings. The table of contents and the chapters themselves have been reorganized to improve the logical flow of the narrative, and the world renowned author team has kept the book fully up to date on the latest research in this fast moving field.},
language = {English},
publisher = {W. W. Norton \& Company},
author = {Gazzaniga, Michael S. and Ivry, Richard B. and Mangun, George R.},
month = oct,
year = {2013}
}
@article{makeig_evolving_2012,
title = {Evolving signal processing for brain–computer interfaces},
volume = {100},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6169943},
number = {Special Centennial Issue},
urldate = {2016-05-11},
journal = {Proceedings of the IEEE},
author = {Makeig, Scott and Kothe, Christian and Mullen, Tim and Bigdely-Shamlo, Nima and Zhang, Zhilin and Kreutz-Delgado, Kenneth},
year = {2012},
pages = {1567--1584},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/DMBG5NP7/abs_all.html:text/html}
}
@inproceedings{ryu_t-less:_2010,
title = {T-less: {A} novel touchless human-machine interface based on infrared proximity sensing},
abstract = {In today's industry, intuitive gesture recognition, as manifested in numerous consumer electronics devices, becomes a main issue of HMI device research. Although finger-tip touch based user interface has paved a main stream in mobile electronics, we envision touch-less HMI as a promising technology in futuristic applications with higher potential in areas where sanity or outdoor operation become of importance. In this paper, we introduce a novel HMI device for non-contact gesture input for intuitive HMI experiences. The enabling technology of the proposed device is the IPA (infrared Proximity Array) sensor by which realtime 3 dimensional depth information can be captured and realized for machine control. For the usability study, two different operating modes are adopted for hand motion inputs: one is a finger tip control mode and the other is a palm control mode. Throughput of the proposed device has been studied and compared to a traditional mouse device for usability evaluation. During the human subject test, the proposed device is found to be useful for PC mouse pointer control. The experimental results are shared in the paper as well.},
booktitle = {Intelligent {Robots} and {Systems} ({IROS})},
author = {Ryu, D. and Um, D. and Tanofsky, P. and Koh, D.H. and Ryu, Y.S. and Kang, S.},
month = oct,
year = {2010},
pages = {5220--5225}
}
@article{sterman_spectral_1996,
title = {Spectral analysis of event-related {EEG} responses during short-term memory performance},
volume = {9},
number = {1},
journal = {Brain Topography},
author = {Sterman, M. Barry and Kaiser, David A. and Veigel, Bettina},
year = {1996},
pages = {21--30}
}
@article{amari_information_2010,
title = {Information geometry in optimization, machine learning and statistical inference},
volume = {5},
number = {3},
journal = {Frontiers of Electrical and Electronic Engineering in China},
author = {Amari, Shun-Ichi},
year = {2010},
pages = {241--260}
}
@article{agueh_barycenters_2011,
title = {Barycenters in the {Wasserstein} space},
volume = {43},
url = {http://epubs.siam.org/doi/abs/10.1137/100805741},
number = {2},
urldate = {2016-03-17},
journal = {SIAM Journal on Mathematical Analysis},
author = {Agueh, Martial and Carlier, Guillaume},
year = {2011},
pages = {904--924},
file = {[PDF] à partir de archives-ouvertes.fr:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/8SXM6VJN/Agueh and Carlier - 2011 - Barycenters in the Wasserstein space.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/2DM3V4K5/100805741.html:text/html}
}
@incollection{lao_canonical_2013,
series = {Lecture {Notes} in {Computer} {Science}},
title = {Canonical {Correlation} {Analysis} {Neural} {Network} for {Steady}-{State} {Visual} {Evoked} {Potentials} {Based} {Brain}-{Computer} {Interfaces}},
volume = {7952},
booktitle = {Advances in {Neural} {Networks} - {ISNN} 2013},
publisher = {Springer},
author = {Lao, KaFai and Wong, ChiMan and Wan, Feng and Mak, PuiIn and Mak, PengUn and Vai, MangI},
editor = {Guo, Chengan and Hou, Zeng-Guang and Zeng, Zhigang},
year = {2013},
pages = {276--283}
}
@article{cecotti_robust_2011,
title = {A robust sensor-selection method for {P}300 brain–computer interfaces},
volume = {8},
url = {http://iopscience.iop.org/article/10.1088/1741-2560/8/1/016001/meta},
number = {1},
urldate = {2016-05-24},
journal = {Journal of neural engineering},
author = {Cecotti, Hubert and Rivet, Bertrand and Congedo, Marco and Jutten, Christian and Bertrand, Olivier and Maby, Emmanuel and Mattout, Jérémie},
year = {2011},
pages = {016001},
file = {[PDF] from archives-ouvertes.fr:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/QC48XTCB/Cecotti et al. - 2011 - A robust sensor-selection method for P300 brain–co.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/TW2CPBI4/meta.html:text/html}
}
@article{zhang_p300_2007,
title = {P300 {Detection} {Using} {Boosting} {Neural} {Networks} with {Application} to {BCI}},
journal = {Complex Medical Engineering, 2007. CME 2007. IEEE/ICME International Conference on},
author = {Zhang, Jia-Cai and Xu, Ya-Qin and Yao, Li},
year = {2007},
pages = {1526--1530}
}
@article{courchesne_stimulus_1975,
title = {Stimulus novelty, task relevance and the visual evoked potential in man},
volume = {39},
number = {2},
journal = {Electroencephalography and Clinical Neurophysiology},
author = {Courchesne, Eric and Hillyard, Steven A. and Galambos, Robert},
year = {1975},
pages = {131--143}
}
@article{tangermann_review_2012,
title = {Review of the {BCI} {Competition} {IV}},
volume = {6},
abstract = {The BCI Competition IV stands in the tradition of prior BCI Competitions that aim to provide high quality neuroscientific data for open access to the scientific community. As experienced already in prior competitions not only scientists from the narrow field of BCI compete, but scholars with a broad variety of backgrounds and nationalities. They include high specialists as well as students. The goals of all BCI Competitions have always been to challenge with respect to novel paradigms and complex data. We report on the following challenges: (1) asynchronous data, (2) synthetic, (3) multi-class continuous data, (4) session-to-session transfer, (5) directionally modulated MEG, (6) finger movements recorded by ECoG. As after past competitions, our hope is that winning entries may enhance the analysis methods of future BCIs.},
number = {55},
journal = {Frontiers in Neuroscience},
author = {Tangermann, Michael and Müller, Klaus-Robert and Aertsen, Ad and Birbaumer, Niels and Braun, Christoph and Brunner, Clemens and Leeb, Robert and Mehring, Carsten and Miller, Kai J and Mueller-Putz, Gernot and Nolte, Guido and Pfurtscheller, Gert and Preissl, Hubert and Schalk, Gerwin and Schlögl, Alois and Vidaurre, Carmen and Waldert, Stephan and Blankertz, Benjamin},
year = {2012}
}
@article{zhang_wavelet_2010,
title = {Wavelet and {Common} {Spatial} {Pattern} for {EEG} signal feature extraction and classification},
volume = {5},
journal = {Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on},
author = {Zhang, Liwei and Liu, Guozhong and Wu, Ying},
year = {2010},
pages = {243--246}
}
@article{rivet_xdawn_2009,
title = {{xDAWN} {Algorithm} to {Enhance} {Evoked} {Potentials}: {Application} to {Brain}-{Computer} {Interface}},
volume = {56},
number = {8},
journal = {Biomedical Engineering, IEEE Transactions on},
author = {Rivet, B. and Souloumiac, A. and Attina, V. and Gibert, G.},
year = {2009},
pages = {2035--2043}
}
@article{gehring_neural_1993,
title = {A neural system for error detection and compensation},
volume = {4},
url = {http://pss.sagepub.com/content/4/6/385.short},
number = {6},
urldate = {2016-04-28},
journal = {Psychological science},
author = {Gehring, William J. and Goss, Brian and Coles, Michael GH and Meyer, David E. and Donchin, Emanuel},
year = {1993},
pages = {385--390},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ERRF83KM/Gehring et al. - 1993 - A neural system for error detection and compensati.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/HB5ES89B/385.html:text/html}
}
@article{mak_optimizing_2011,
title = {Optimizing the {P}300-based brain–computer interface: current status, limitations and future directions},
volume = {8},
shorttitle = {Optimizing the {P}300-based brain–computer interface},
url = {http://iopscience.iop.org/article/10.1088/1741-2560/8/2/025003/meta},
number = {2},
urldate = {2016-05-24},
journal = {Journal of neural engineering},
author = {Mak, J. N. and Arbel, Y. and Minett, J. W. and McCane, L. M. and Yuksel, B. and Ryan, D. and Thompson, D. and Bianchi, L. and Erdogmus, D.},
year = {2011},
pages = {025003},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/D6J3M47U/Mak et al. - 2011 - Optimizing the P300-based brain–computer interface.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/93QWR65N/meta.html:text/html}
}
@incollection{chaudhary_survey_2011,
title = {A {Survey} on {Hand} {Gesture} {Recognition} in {Context} of {Soft} {Computing} {Advanced} {Computing}},
volume = {133},
abstract = {Hand gestures recognition is the natural way of Human Machine interaction and today many researchers in the academia and industry are interested in this direction. It enables human being to interact with machine very easily and conveniently without wearing any extra device. It can be applied from sign language recognition to robot control and from virtual reality to intelligent home systems. In this paper we are discussing work done in the area of hand gesture recognition where focus is on the soft computing based methods like artificial neural network, fuzzy logic, genetic algorithms, etc. We also described hand detection methods in the preprocessed image for detecting the hand image. Most researchers used fingertips for hand detection in appearance based modeling. Finally we are comparing results given by different researchers after their implementation.},
booktitle = {Communications in {Computer} and {Information} {Science}},
author = {Chaudhary, A. and Raheja, J.L. and Das, K. and Raheja, S.},
year = {2011},
pages = {46--55}
}
@article{faradji_brain-computer_2009,
title = {A brain-computer interface based on mental tasks with a zero false activation rate},
journal = {Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on},
author = {Faradji, F. and Ward, R.K. and Birch, G.E.},
year = {2009},
pages = {355--358}
}
@incollection{allison_could_2010-1,
series = {Human-{Computer} {Interaction} {Series}},
title = {Could {Anyone} {Use} a {BCI}?},
booktitle = {Brain-{Computer} {Interfaces}},
publisher = {Springer London},
author = {Allison, Brendan Z. and Neuper, Christa},
editor = {Tan, Desney S. and Nijholt, Anton},
year = {2010},
pages = {35--54}
}
@article{brunner_spatial_2007,
title = {Spatial filtering and selection of optimized components in four class motor imagery {EEG} data using independent components analysis},
volume = {28},
number = {8},
journal = {Pattern Recognition Letters},
author = {Brunner, Clemens and Naeem, Muhammad and Leeb, Robert and Graimann, Bernhard and Pfurtscheller, Gert},
year = {2007},
pages = {957--964}
}
@article{iacoviello_real-time_2015,
title = {A real-time classification algorithm for {EEG}-based {BCI} driven by self-induced emotions},
volume = {122},
issn = {0169-2607},
url = {http://www.sciencedirect.com/science/article/pii/S0169260715002217},
doi = {10.1016/j.cmpb.2015.08.011},
abstract = {Background and objective
The aim of this paper is to provide an efficient, parametric, general, and completely automatic real time classification method of electroencephalography (EEG) signals obtained from self-induced emotions. The particular characteristics of the considered low-amplitude signals (a self-induced emotion produces a signal whose amplitude is about 15\% of a really experienced emotion) require exploring and adapting strategies like the Wavelet Transform, the Principal Component Analysis (PCA) and the Support Vector Machine (SVM) for signal processing, analysis and classification. Moreover, the method is thought to be used in a multi-emotions based Brain Computer Interface (BCI) and, for this reason, an ad hoc shrewdness is assumed.
Method
The peculiarity of the brain activation requires ad-hoc signal processing by wavelet decomposition, and the definition of a set of features for signal characterization in order to discriminate different self-induced emotions. The proposed method is a two stages algorithm, completely parameterized, aiming at a multi-class classification and may be considered in the framework of machine learning. The first stage, the calibration, is off-line and is devoted at the signal processing, the determination of the features and at the training of a classifier. The second stage, the real-time one, is the test on new data. The PCA theory is applied to avoid redundancy in the set of features whereas the classification of the selected features, and therefore of the signals, is obtained by the SVM.
Results
Some experimental tests have been conducted on EEG signals proposing a binary BCI, based on the self-induced disgust produced by remembering an unpleasant odor. Since in literature it has been shown that this emotion mainly involves the right hemisphere and in particular the T8 channel, the classification procedure is tested by using just T8, though the average accuracy is calculated and reported also for the whole set of the measured channels.
Conclusions
The obtained classification results are encouraging with percentage of success that is, in the average for the whole set of the examined subjects, above 90\%. An ongoing work is the application of the proposed procedure to map a large set of emotions with EEG and to establish the EEG headset with the minimal number of channels to allow the recognition of a significant range of emotions both in the field of affective computing and in the development of auxiliary communication tools for subjects affected by severe disabilities.},
number = {3},
urldate = {2016-05-03},
journal = {Computer Methods and Programs in Biomedicine},
author = {Iacoviello, Daniela and Petracca, Andrea and Spezialetti, Matteo and Placidi, Giuseppe},
month = dec,
year = {2015},
keywords = {Affective computing, BCI, Classification algorithm, EEG signals, Principal components analysis, Self-induced emotions},
pages = {293--303},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/92KZQ3BE/Iacoviello et al. - 2015 - A real-time classification algorithm for EEG-based.pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/4JHSQ6H5/S0169260715002217.html:text/html}
}
@article{wolpaw_brain-computer_2002,
title = {Brain-computer interfaces for communication and control},
volume = {113},
number = {6},
journal = {Clinical Neurophysiology},
author = {Wolpaw, Jonathan R. and Birbaumer, Niels and McFarland, Dennis J. and Pfurtscheller, Gert and Vaughan, Theresa M.},
year = {2002},
keywords = {Brain Diseases, Communication Aids for Disabled, Computer Systems, Electroencephalography, Humans, User-Computer Interface},
pages = {767--791}
}
@article{mattout_improving_2013,
title = {Improving non-invasive {BCI} for possible clinical application: {Example} of the “{P}300-speller”},
volume = {56},
issn = {18770657},
shorttitle = {Improving non-invasive {BCI} for possible clinical application},
url = {http://linkinghub.elsevier.com/retrieve/pii/S1877065713010804},
doi = {10.1016/j.rehab.2013.07.963},
language = {en},
urldate = {2016-04-21},
journal = {Annals of Physical and Rehabilitation Medicine},
author = {Mattout, J. and Perrin, M. and Bertrand, O. and Maby, E.},
month = oct,
year = {2013},
pages = {e374}
}
@article{guan_high_2004,
title = {High performance {P}300 speller for brain-computer interface},
journal = {Biomedical Circuits and Systems, 2004 IEEE International Workshop on},
author = {Guan, Cuntai and Thulasidas, Manoj and Wu, Jiankang},
year = {2004},
pages = {S3/5/INV -- S3/13--16}
}
@article{matthews_functional_2004,
title = {Functional magnetic resonance imaging},
volume = {75},
issn = {, 1468-330X},
url = {http://jnnp.bmj.com/content/75/1/6},
abstract = {Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a powerful approach to defining activity in the healthy and diseased human brain. BOLD fMRI detects local increases in relative blood oxygenation that are most probably a direct consequence of neurotransmitter action and thus reflect local neuronal signalling. The method allows localisation to volumes of the order of a few to several cubic millimetres and can be used in serial studies of individual subjects. Basic approaches to experimental design and analysis are reviewed briefly, as well as potential clinical applications. The latter include three broad areas: anatomical characterisation of normal or pathological patterns of brain functioning; distinguishing pathological traits; and monitoring treatment responses. New research is emphasising the integration of fMRI with other techniques, particularly electrophysiological. In conjunction with MRI methods for characterising pathological load, fMRI promises a refined understanding of when disease processes begin and how they can be modified by new treatments.},
language = {en},
number = {1},
urldate = {2016-04-19},
journal = {Journal of Neurology, Neurosurgery \& Psychiatry},
author = {Matthews, P. M. and Jezzard, P.},
month = jan,
year = {2004},
pmid = {14707297},
keywords = {ASL, arterial spin labelling, BOLD, blood oxygenation level dependent, brain plasticity, EPI, echo planar imaging, fMRI, functional magnetic resonance imaging, functional imaging, magnetic resonance, MEG, magnetoencephalography, TMS, transcranial magnetic stimulation, treatment monitoring},
pages = {6--12},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/F3G9PR5Q/Matthews and Jezzard - 2004 - Functional magnetic resonance imaging.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/D37G286A/6.html:text/html}
}
@article{cecotti_convolutional_2008,
title = {Convolutional {Neural} {Network} with embedded {Fourier} {Transform} for {EEG} classification},
journal = {Pattern Recognition, 2008. ICPR 2008. 19th International Conference on},
author = {Cecotti, H. and Graeser, A.},
year = {2008},
pages = {1--4}
}
@inproceedings{barachant_bci_2012,
title = {{BCI} {Signal} {Classification} using a {Riemannian}-based kernel},
booktitle = {Proceeding of the 20th {European} {Symposium} on {Artificial} {Neural} {Networks}, {Computational} {Intelligence} and {Machine} {Learning}},
author = {Barachant, Alexandre and Bonnet, Stéphane and Congedo, Marco and Jutten, Christian and {others}},
year = {2012},
pages = {97--102}
}
@article{coyle_optical_2004,
title = {An optical brain computer interface},
url = {http://eprints.maynoothuniversity.ie/1275},
urldate = {2016-04-19},
author = {Coyle, S. and Ward, Tomas and Markham, Charles},
year = {2004},
file = {[PDF] from maynoothuniversity.ie:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/IAU8A2E3/Coyle et al. - 2004 - An optical brain computer interface.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/P7H9JZ4D/1275.html:text/html}
}
@article{serruya_brain-machine_2002,
title = {Brain-machine interface: {Instant} neural control of a movement signal},
volume = {416},
copyright = {© 2002 Nature Publishing Group},
issn = {0028-0836},
shorttitle = {Brain-machine interface},
url = {http://www.nature.com/nature/journal/v416/n6877/full/416141a.html},
doi = {10.1038/416141a},
abstract = {Hands-free operation of a cursor can be achieved by a few neurons in the motor cortex.
The activity of motor cortex (MI) neurons conveys movement intent sufficiently well to be used as a control signal to operate artificial devices, but until now this has called for extensive training or has been confined to a limited movement repertoire. Here we show how activity from a few (7–30) MI neurons can be decoded into a signal that a monkey is able to use immediately to move a computer cursor to any new position in its workspace (14° 14° visual angle). Our results, which are based on recordings made by an electrode array that is suitable for human use, indicate that neurally based control of movement may eventually be feasible in paralysed humans.},
language = {en},
number = {6877},
urldate = {2016-04-18},
journal = {Nature},
author = {Serruya, Mijail D. and Hatsopoulos, Nicholas G. and Paninski, Liam and Fellows, Matthew R. and Donoghue, John P.},
month = mar,
year = {2002},
pages = {141--142},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/KZX83KND/Serruya et al. - 2002 - Brain-machine interface Instant neural control of.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/ABS67AIC/416141a.html:text/html}
}
@article{berger_uber_1929,
title = {Über das {Elektrenkephalogramm} des {Menschen}},
volume = {87},
issn = {0003-9373, 1433-8491},
url = {http://link.springer.com/article/10.1007/BF01797193},
doi = {10.1007/BF01797193},
language = {de},
number = {1},
urldate = {2016-04-12},
journal = {Archiv für Psychiatrie und Nervenkrankheiten},
author = {Berger, Professor Dr Hans},
month = dec,
year = {1929},
keywords = {Neurology, Neurosciences, Psychiatry},
pages = {527--570},
file = {Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/WJNFGS34/Berger - 1929 - Über das Elektrenkephalogramm des Menschen.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/X9BCKIPK/10.html:text/html}
}
@article{pfurtscheller_spatiotemporal_2003,
title = {Spatiotemporal patterns of beta desynchronization and gamma synchronization in corticographic data during self-paced movement},
volume = {114},
url = {http://www.sciencedirect.com/science/article/pii/S1388245703000671},
number = {7},
urldate = {2016-04-15},
journal = {Clinical neurophysiology},
author = {Pfurtscheller, Gert and Graimann, Bernard and Huggins, Jane E. and Levine, Simon P. and Schuh, Lori A.},
year = {2003},
pages = {1226--1236},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/JWFF5IU2/Pfurtscheller et al. - 2003 - Spatiotemporal patterns of beta desynchronization .pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/F3UFER2I/S1388245703000671.html:text/html}
}
@article{nicolas-alonso_brain_2012,
title = {Brain {Computer} {Interfaces}, a {Review}},
volume = {12},
number = {2},
journal = {Sensors},
author = {{Nicolas-Alonso} and Fernando, Luis and Gomez-Gil, Jaime},
year = {2012},
pages = {1211--1279}
}
@article{sitaram_fmri_2007,
title = {{fMRI} {Brain}-{Computer} {Interface}: {A} {Tool} for {Neuroscientific} {Research} and {Treatment}},
volume = {2007},
issn = {1687-5265},
shorttitle = {{fMRI} {Brain}-{Computer} {Interface}},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2233807/},
doi = {10.1155/2007/25487},
abstract = {Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available and applicable. This noninvasive technique could potentially complement the traditional neuroscientific experimental methods by varying the activity of the neural substrates of a region of interest as an independent variable to study its effects on behavior. If the neurobiological basis of a disorder (e.g., chronic pain, motor diseases, psychopathy, social phobia, depression) is known in terms of abnormal activity in certain regions of the brain, fMRI-BCI can be targeted to modify activity in those regions with high specificity for treatment. In this paper, we review recent results of the application of fMRI-BCI to neuroscientific research and psychophysiological treatment.},
urldate = {2016-04-20},
journal = {Computational Intelligence and Neuroscience},
author = {Sitaram, Ranganatha and Caria, Andrea and Veit, Ralf and Gaber, Tilman and Rota, Giuseppina and Kuebler, Andrea and Birbaumer, Niels},
year = {2007},
pmid = {18274615},
pmcid = {PMC2233807},
file = {PubMed Central Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/RRXQGGW7/Sitaram et al. - 2007 - fMRI Brain-Computer Interface A Tool for Neurosci.pdf:application/pdf}
}
@article{nielsen_sided_2009,
title = {Sided and symmetrized {Bregman} centroids},
volume = {55},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4957641},
number = {6},
urldate = {2016-06-23},
journal = {IEEE transactions on Information Theory},
author = {Nielsen, Frank and Nock, Richard},
year = {2009},
pages = {2882--2904},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/D5Q6C37T/login.html:text/html}
}
@article{abdulkader_brain_2015,
title = {Brain computer interfacing: {Applications} and challenges},
volume = {16},
shorttitle = {Brain computer interfacing},
url = {http://www.sciencedirect.com/science/article/pii/S1110866515000237},
number = {2},
urldate = {2016-05-30},
journal = {Egyptian Informatics Journal},
author = {Abdulkader, Sarah N. and Atia, Ayman and Mostafa, Mostafa-Sami M.},
year = {2015},
pages = {213--230},
file = {[HTML] from sciencedirect.com:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/3R7RE4RW/S1110866515000237.html:text/html}
}
@article{sutton_information_1967,
title = {Information {Delivery} and the {Sensory} {Evoked} {Potential}},
volume = {155},
number = {3768},
journal = {Science},
author = {Sutton, Samuel and Tueting, Patricia and Zubin, Joseph and John, E. R.},
year = {1967},
pages = {1436--1439}
}
@article{treder_gaze-independent_2011,
title = {Gaze-independent brain–computer interfaces based on covert attention and feature attention},
volume = {8},
url = {http://iopscience.iop.org/article/10.1088/1741-2560/8/6/066003/meta},
number = {6},
urldate = {2016-04-28},
journal = {Journal of neural engineering},
author = {Treder, Matthias Sebastian and Schmidt, Nico Maurice and Blankertz, Benjamin},
year = {2011},
pages = {066003},
file = {[HTML] from iop.org:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/2GUMRQD6/066003.html:text/html;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/Z9TD3DE3/meta.html:text/html}
}
@article{bundy_decoding_2016,
title = {Decoding three-dimensional reaching movements using electrocorticographic signals in humans},
volume = {13},
issn = {1741-2552},
url = {http://stacks.iop.org/1741-2552/13/i=2/a=026021},
doi = {10.1088/1741-2560/13/2/026021},
abstract = {Objective. Electrocorticography (ECoG) signals have emerged as a potential control signal for brain–computer interface (BCI) applications due to balancing signal quality and implant invasiveness. While there have been numerous demonstrations in which ECoG signals were used to decode motor movements and to develop BCI systems, the extent of information that can be decoded has been uncertain. Therefore, we sought to determine if ECoG signals could be used to decode kinematics (speed, velocity, and position) of arm movements in 3D space. Approach. To investigate this, we designed a 3D center-out reaching task that was performed by five epileptic patients undergoing temporary placement of ECoG arrays. We used the ECoG signals within a hierarchical partial-least squares (PLS) regression model to perform offline prediction of hand speed, velocity, and position. Main Results. The hierarchical PLS regression model enabled us to predict hand speed, velocity, and position during 3D reaching movements from held-out test sets with accuracies above chance in each patient with mean correlation coefficients between 0.31 and 0.80 for speed, 0.27 and 0.54 for velocity, and 0.22 and 0.57 for position. While beta band power changes were the most significant features within the model used to classify movement and rest, the local motor potential and high gamma band power changes, were the most important features in the prediction of kinematic parameters. Significance. We believe that this study represents the first demonstration that truly three-dimensional movements can be predicted from ECoG recordings in human patients. Furthermore, this prediction underscores the potential to develop BCI systems with multiple degrees of freedom in human patients using ECoG.},
language = {en},
number = {2},
urldate = {2016-04-15},
journal = {Journal of Neural Engineering},
author = {Bundy, David T. and Pahwa, Mrinal and Szrama, Nicholas and Leuthardt, Eric C.},
year = {2016},
pages = {026021},
file = {IOP Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/PWCNHMD7/Bundy et al. - 2016 - Decoding three-dimensional reaching movements usin.pdf:application/pdf}
}
@article{mohamed_single-trial_2011,
title = {Single-trial {EEG} discrimination between wrist and finger movement imagery and execution in a sensorimotor {BCI}},
journal = {Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE},
author = {Mohamed, A.K. and Marwala, T. and John, L.R.},
year = {2011},
pages = {6289--6293}
}
@article{hassan_classification_2008,
title = {Classification of the {Imagination} of the {Left} and {Right} {Hand} {Movements} using {EEG}},
journal = {Biomedical Engineering Conference, 2008. CIBEC 2008. Cairo International},
author = {Hassan, M.A. and Ali, A.F. and Eladawy, M.I.},
year = {2008},
pages = {1--5}
}
@article{polich_updating_2007,
title = {Updating {P}300: an integrative theory of {P}3a and {P}3b.},
volume = {118},
number = {10},
journal = {Clinical Neurophysiology},
author = {Polich, John},
year = {2007},
pages = {2128--2148}
}
@article{fazli_ensembles_2008,
title = {Ensembles of temporal filters enhance classification performance for {ERD}-based {BCI} systems},
journal = {Proceedings of the 4th International Brain-Computer Interface Workshop and Training Course},
author = {Fazli, S. and Grozea, C. and Danaczy, M. and Blankertz, B. and Muller, K. R. and Popescu, F.},
year = {2008}
}
@article{ramoser_optimal_2000,
title = {Optimal spatial filtering of single trial {EEG} during imagined hand movement},
volume = {8},
journal = {IEEE Transactions on Neural Systems and Rehabilitation},
author = {Ramoser, H. and Müller-Gerking, Johannes and Pfurtscheller, G.},
year = {2000},
pages = {441--446}
}
@article{kennedy_direct_2000,
title = {Direct control of a computer from the human central nervous system},
volume = {8},
url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=847815},
number = {2},
urldate = {2016-04-18},
journal = {Rehabilitation Engineering, IEEE Transactions on},
author = {Kennedy, Philip R. and Bakay, Roy AE and Moore, Melody M. and Adams, Kim and Goldwaithe, John},
year = {2000},
pages = {198--202},
file = {[PDF] from researchgate.net:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/CU35KJ6T/Kennedy et al. - 2000 - Direct control of a computer from the human centra.pdf:application/pdf;Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/2I4QNSXM/login.html:text/html}
}
@article{gramfort_mne_2014,
title = {{MNE} software for processing {MEG} and {EEG} data},
volume = {86},
issn = {1053-8119},
url = {http://www.sciencedirect.com/science/article/pii/S1053811913010501},
doi = {10.1016/j.neuroimage.2013.10.027},
abstract = {Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne.},
urldate = {2016-04-21},
journal = {NeuroImage},
author = {Gramfort, Alexandre and Luessi, Martin and Larson, Eric and Engemann, Denis A. and Strohmeier, Daniel and Brodbeck, Christian and Parkkonen, Lauri and Hämäläinen, Matti S.},
month = feb,
year = {2014},
keywords = {Connectivity, Electroencephalography (EEG), Inverse problem, Magnetoencephalography (MEG), Non-parametric statistics, Software, Time–frequency analysis},
pages = {446--460},
file = {ScienceDirect Full Text PDF:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/4BF5F73U/Gramfort et al. - 2014 - MNE software for processing MEG and EEG data.pdf:application/pdf;ScienceDirect Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/FC38K8AQ/S1053811913010501.html:text/html}
}
@article{moakher_differential_2005,
title = {A differential geometric approach to the geometric mean of symmetric positive-definite matrices},
volume = {26},
number = {3},
journal = {SIAM Journal on Matrix Analysis and Applications},
author = {Moakher, Maher},
year = {2005},
pages = {735--747}
}
@article{blankertz_single_2002,
title = {Single {Trial} {Detection} of {EEG} {Error} {Potentials}: {A} {Tool} for {Increasing} {BCI} {Transmission} {Rates}},
volume = {2415},
journal = {Artificial Neural Networks ICANN 2002},
author = {Blankertz, Benjamin and Schaefer, Christin and Dornhege, Guido and Curio, Gabriel},
year = {2002},
pages = {1137--1143}
}
@article{puce_multiple_2013,
title = {Multiple faces elicit augmented neural activity},
volume = {7},
url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3682123/},
urldate = {2016-02-01},
journal = {Frontiers in human neuroscience},
author = {Puce, Aina and McNeely, Marie E. and Berrebi, Michael E. and Thompson, James C. and Hardee, Jillian and Brefczynski-Lewis, Julie},
year = {2013},
file = {[HTML] from nih.gov:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/VFTFQUT8/PMC3682123.html:text/html}
}
@article{zander_towards_2011-1,
title = {Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general},
volume = {8},
number = {2},
journal = {Journal of Neural Engineering},
author = {Zander, Thorsten O. and Kothe, Christian},
year = {2011},
pages = {025005+}
}
@article{kalunga_online_2016,
title = {Online {SSVEP}-based {BCI} using {Riemannian} geometry},
url = {http://www.sciencedirect.com/science/article/pii/S0925231216000540},
urldate = {2016-03-09},
journal = {Neurocomputing},
author = {Kalunga, Emmanuel K. and Chevallier, Sylvain and Barthélemy, Quentin and Djouani, Karim and Monacelli, Eric and Hamam, Yskandar},
year = {2016},
file = {Snapshot:/home/emmanuelkalunga/.mozilla/firefox/05w9y9qn.default/zotero/storage/JNGJDIQD/S0925231216000540.html:text/html}
}
