deletions | additions       diff --git a/section_Review_of_Related_Literature__.tex b/section_Review_of_Related_Literature__.tex  index 938a136..17b27f1 100644  --- a/section_Review_of_Related_Literature__.tex  +++ b/section_Review_of_Related_Literature__.tex 
...
\subsection{Related Studies on EMG used in Computer Science}  \subsection{Related Studies on Machine Learning in processing EMG based gestures}  Several studies related to EMG pattern recognition have been conducted over the past decades. These techniques have been used to analyze EMG signals which have been complex to recognize due to large variations  in a computationally efficient manner. signals.  In a study conducted by Liu et al.\cite{Liu_2007}, a novel EMG classifier called cascaded kernel learning machine (CKLM) was proven to be effective, achieving a high recognition rate of 93.54\%. The study employed a cascaded architecture of kernel learning machines including the General Discriminant Analysis (GDA), and the support vector machine (SVM) which offers classification performance that matches or exceeds other classifiers and does so in a computationally efficient manner \cite{Oskoei_2008}.