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Reseach Article

A Technical Review on Statistical Feature Extraction of ECG signal

Published on None 2011 by Asutosh Kar, Leena Das
2nd National Conference on Computing, Communication and Sensor Network
Foundation of Computer Science USA
CCSN - Number 2
None 2011
Authors: Asutosh Kar, Leena Das
9c962a0e-575b-4c75-8217-bc6a0183ae83

Asutosh Kar, Leena Das . A Technical Review on Statistical Feature Extraction of ECG signal. 2nd National Conference on Computing, Communication and Sensor Network. CCSN, 2 (None 2011), 35-40.

@article{
author = { Asutosh Kar, Leena Das },
title = { A Technical Review on Statistical Feature Extraction of ECG signal },
journal = { 2nd National Conference on Computing, Communication and Sensor Network },
issue_date = { None 2011 },
volume = { CCSN },
number = { 2 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 35-40 },
numpages = 6,
url = { /specialissues/ccsn/number2/4177-ccsn015/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 2nd National Conference on Computing, Communication and Sensor Network
%A Asutosh Kar
%A Leena Das
%T A Technical Review on Statistical Feature Extraction of ECG signal
%J 2nd National Conference on Computing, Communication and Sensor Network
%@ 0975-8887
%V CCSN
%N 2
%P 35-40
%D 2011
%I International Journal of Computer Applications
Abstract

ECG Feature Extraction plays a significant role in diagnosing most of the cardiac diseases. In this paper a comprehensive review has been made for statistical feature extraction of ECG signal analyzing classifying method which have been proposed during the last decade and under evaluation that includes digital signal analysis, Fuzzy Logic methods, Artificial Neural Network, Hidden Markov Model, Genetic Algorithm, Support Vector Machines, Self-Organizing Map, Bayesian and other method with each approach exhibiting its own advantages and disadvantages. To diagnose the condition of the heart Electrocardiography is an important tool but it is a time consuming process to analyze a long duration ECG signal as it may contain thousands of heart beats. Hence it is desired to automate the entire process of heart beat classification and preferably diagnose it accurately. For subsequent analysis of ECG signals its fundamental features like amplitudes and intervals are required which determine the functioning of heart.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Neural Network ECG Signal Fuzzy logic