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A Robust R-peak Detection Algorithm using Wavelet Packets

by Omkar Singh, Ramesh Kumar Sunkaria
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 36 - Number 5
Year of Publication: 2011
Authors: Omkar Singh, Ramesh Kumar Sunkaria
10.5120/4489-6319

Omkar Singh, Ramesh Kumar Sunkaria . A Robust R-peak Detection Algorithm using Wavelet Packets. International Journal of Computer Applications. 36, 5 ( December 2011), 37-43. DOI=10.5120/4489-6319

@article{ 10.5120/4489-6319,
author = { Omkar Singh, Ramesh Kumar Sunkaria },
title = { A Robust R-peak Detection Algorithm using Wavelet Packets },
journal = { International Journal of Computer Applications },
issue_date = { December 2011 },
volume = { 36 },
number = { 5 },
month = { December },
year = { 2011 },
issn = { 0975-8887 },
pages = { 37-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume36/number5/4489-6319/ },
doi = { 10.5120/4489-6319 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:22:23.675043+05:30
%A Omkar Singh
%A Ramesh Kumar Sunkaria
%T A Robust R-peak Detection Algorithm using Wavelet Packets
%J International Journal of Computer Applications
%@ 0975-8887
%V 36
%N 5
%P 37-43
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The efficient detection of R-peaks in electrocardiogram (ECG) signal is extremely important for its further processing with regard to cardiac health monitoring. In this paper, an efficient R-peak detection algorithm based on wavelet packets has been proposed. The wavelet packets decompose ECG signal into different frequency subbands of uniform bandwidth. The features evaluated from a set of subbands are combined with heuristic detection strategy for beat detection. The proposed R-peak detection algorithm was tested on different data records of standard data bases Fantasia database, MIT-BIH arrhythmia database and self-recorded signals. A sensitivity S_e= 100% and a positive predictivity of +P = 100% for Fantasia database and S_e= 100%, +P = 100% for self-recorded signals and S_e = 99.94%, +P = 99.93% for MIT-BIH arrhythmia database were achieved using this proposed algorithm.

References
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Index Terms

Computer Science
Information Sciences

Keywords

R-peak detection ECG Wavelet packets Sensitivity Positive predictivity

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