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Development of derivative based algorithm for the detection of QRS-complexes in Single lead Electrocardiogram using FCM

Published on December 2011 by Swati Sharma, S. S. Mehta, Harleen Mehta
International Conference on Electronics, Information and Communication Engineering
Foundation of Computer Science USA
ICEICE - Number 4
December 2011
Authors: Swati Sharma, S. S. Mehta, Harleen Mehta
916dd379-5347-48e1-a97a-5daf1f21b948

Swati Sharma, S. S. Mehta, Harleen Mehta . Development of derivative based algorithm for the detection of QRS-complexes in Single lead Electrocardiogram using FCM. International Conference on Electronics, Information and Communication Engineering. ICEICE, 4 (December 2011), 19-23.

@article{
author = { Swati Sharma, S. S. Mehta, Harleen Mehta },
title = { Development of derivative based algorithm for the detection of QRS-complexes in Single lead Electrocardiogram using FCM },
journal = { International Conference on Electronics, Information and Communication Engineering },
issue_date = { December 2011 },
volume = { ICEICE },
number = { 4 },
month = { December },
year = { 2011 },
issn = 0975-8887,
pages = { 19-23 },
numpages = 5,
url = { /specialissues/iceice/number4/4275-iceice029/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 International Conference on Electronics, Information and Communication Engineering
%A Swati Sharma
%A S. S. Mehta
%A Harleen Mehta
%T Development of derivative based algorithm for the detection of QRS-complexes in Single lead Electrocardiogram using FCM
%J International Conference on Electronics, Information and Communication Engineering
%@ 0975-8887
%V ICEICE
%N 4
%P 19-23
%D 2011
%I International Journal of Computer Applications
Abstract

FCM algorithm is used to divide the ECG signal into QRS and non-QRS region. This paper presents a simple technique for automatic detection of cardiac beat (QRS-complex) in Electrocardiogram (ECG) using Fuzzy C-Means (FCM) clustering algorithm. The power line interference and baseline wander present in the ECG signal is removed using digital filtering techniques. Absolute derivative of the filtered ECG signal is calculated to enhance the QRS-complexes in the ECG signal. Algorithm performance is validated using original single lead ECG recordings from the CSE ECG database. Detection rate of 98.32% with 1.68% of false negative (FN) and 0.08% of false positive (FP) has been achieved.

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Index Terms

Computer Science
Information Sciences

Keywords

ECG QRS-complex ECG detection FCM