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Total Variation Denoising Based Approach for R-peak Detection in ECG Signals

Publication Type : Conference Paper

Publisher : Elsevier Procedia Computer Science

Source : ICACC, Elsevier Procedia Computer Science, 2016 (Scopus)

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Keywords : Biomedical signal processing, Cardiac monitoring, Electrocardiography, False negatives, False positive, Image denoising, Overall accuracies, Predictivity, R-peak detection, Shannon, Signal denoising, Signal detection, Total variation

Campus : Amritapuri, Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Center for Computational Engineering and Networking (CEN), Electronics and Communication

Year : 2016

Abstract : Detecting R-peak signal from electrocardiogram or ECG signal plays a vital role in cardiac monitoring system and ECG applications. In this paper, Total Variation Denoising (TVD) based approach is proposed to find the locations of R-peaks in the ECG signal. One advantage of using TVD method is that it preserves the sharp slopes or the peaks in the signal. This motivated to use TVD method for R-peak detection problem. The proposed approach is evaluated using the first channel, 48 ECG records from MIT-BIH Arrhythmia database. The accuracy of TVD based approach is calculated on all the 48 records. The proposed method gives 9 false-negative or FN beats, 126 false-positive or FP beats, positive-predictivity of 99.885%, sensitivity of 99.914%, with an overall accuracy of 99.79%. © 2016 The Authors. Published by Elsevier B.V.

Cite this Research Publication : Sachin Kumar S, Neethu Mohan, Prabaharan P, KP Soman, Total Variation Denoising based Approach for R-peak Detection in ECG Signals, ICACC, Elsevier Procedia Computer Science, 2016 (Scopus)

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