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

Publication Type : Journal

Publisher : Procedia Computer Science, Elsevier.

Source : Procedia Computer Science, Elsevier, Volume 93, p.697-705 (2016)

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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

School : School of Engineering

Center : Cyber Security

Department : CISAI

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 : S. Sa Kumar, Dr. Neethu Mohan, Prabaharan, Pb, Dr. Soman K. P., J., M., and J., J., “Total Variation Denoising Based Approach for R-peak Detection in ECG Signals”, in Procedia Computer Science, 2016, vol. 93, pp. 697-705.

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