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Reseach Article

A Survey Approach on ECG Feature Extraction Techniques

by Shalini Sahay, A.k.wadhwani, Sulochana Wadhwani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 11
Year of Publication: 2015
Authors: Shalini Sahay, A.k.wadhwani, Sulochana Wadhwani
10.5120/21268-4002

Shalini Sahay, A.k.wadhwani, Sulochana Wadhwani . A Survey Approach on ECG Feature Extraction Techniques. International Journal of Computer Applications. 120, 11 ( June 2015), 1-4. DOI=10.5120/21268-4002

@article{ 10.5120/21268-4002,
author = { Shalini Sahay, A.k.wadhwani, Sulochana Wadhwani },
title = { A Survey Approach on ECG Feature Extraction Techniques },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 11 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number11/21268-4002/ },
doi = { 10.5120/21268-4002 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:05:54.618908+05:30
%A Shalini Sahay
%A A.k.wadhwani
%A Sulochana Wadhwani
%T A Survey Approach on ECG Feature Extraction Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 11
%P 1-4
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

ECG Feature Extraction plays a significant role in diagnosing most of the cardiac diseases. One cardiac cycle in an ECG signal consists of the P-QRS-T waves. This feature extraction scheme determines the amplitudes and intervals in the ECG signal for subsequent analysis. The amplitudes and intervals value of P-QRS-T segment determines the functioning of heart of every human. Recently, numerous research and techniques have been developed for analyzing the ECG signal. For subsequent analysis of ECG signals its fundamental features like amplitudes and intervals are required which determine the functioning of heart. The proposed schemes were mostly based on Fuzzy Logic Methods, Artificial Neural Networks (ANN), Genetic Algorithm (GA), Support Vector Machines (SVM), and other Signal Analysis techniques. All these techniques and algorithms have their advantages and limitations. This proposed paper discusses various techniques and transformations proposed earlier in literature for extracting feature from an ECG signal.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Neural Networks (ANN) Cardiac Cycle ECG signal Feature Extraction Fuzzy Logic Genetic Algorithm