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Detection and Classification of Atrial and Ventricular Cardiovascular Diseases to Improve the Cardiac Health Literacy for Resource Constrained Regions
  • Neha Arora,
  • Biswajit Mishra
Neha Arora
Dhirubhai Ambani Institute of Information and Communication Technology
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Biswajit Mishra
Dhirubhai Ambani Institute of Information and Communication Technology

Corresponding Author:biswajit_mishra@daiict.ac.in

Author Profile


ECG is a non-invasive way of determining cardiac health by measuring the electrical activity of the heart. We investigate a novel detection technique for feature points P, QRS and T to diagnose various atrial and ventricular cardiovascular anomalies with ECG signals for ambulatory monitoring. Before the system is worthy of field trials, we validated it with several databases and recorded their response. The QRS complex detection is based on the Pan Tompkins Algorithm and difference operation method that provides positive predictivity, sensitivity and false detection rate of 99.29\%, 99.49\% and 1.29 \% respectively. Proposed novel T wave detection provides sensitivity of 97.78\%. Also, proposed P wave detection provides positive predictivity, sensitivity and false detection rate of 99.43\%, 99.4\% and 1.15\% for the control study (normal subjects) and 82.68\%, 94.3\% and 25.4\% for the case (patients with cardiac anomalies) study respectively. Disease detection such as, arrhythmia is based on standard R-R intervals while myocardial infarction is based on the ST-T deviations where the positive predictivity, sensitivity and accuracy are observed to be 94.6\%, 84.2\% and 85\%, respectively. It should be noted that, since the frontal leads are only used, the anterior myocardial infarction cases are detected with the injury pattern in lead \textit{avl} and ST depression in reciprocal leads. Detection of atrial fibrillation is done for both short and long duration signals using statistical methods using interquartile range and standard deviations, giving very high accuracy, 100\% in most cases. The system hardware for obtaining the 2 lead ECG signal is designed using commercially available off the shelf components. Small field validation of the designed system is performed at a Public Health Centre in Gujarat, India with 42 patients (both cases and controls). We achieved 78.5\% accuracy during the field validation.
21 Jan 2023Submitted to Healthcare Technology Letters
23 Jan 2023Submission Checks Completed
23 Jan 2023Assigned to Editor
24 Jan 2023Reviewer(s) Assigned
21 Feb 2023Review(s) Completed, Editorial Evaluation Pending
21 Feb 2023Editorial Decision: Revise Major
02 Mar 20231st Revision Received
07 Mar 2023Submission Checks Completed
07 Mar 2023Assigned to Editor
10 Mar 2023Reviewer(s) Assigned
21 Mar 2023Review(s) Completed, Editorial Evaluation Pending
23 Mar 2023Editorial Decision: Accept