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A Study on ECG Signal Classification Techniques

by R. Kavitha, T Christopher
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 14
Year of Publication: 2014
Authors: R. Kavitha, T Christopher
10.5120/15052-3398

R. Kavitha, T Christopher . A Study on ECG Signal Classification Techniques. International Journal of Computer Applications. 86, 14 ( January 2014), 9-14. DOI=10.5120/15052-3398

@article{ 10.5120/15052-3398,
author = { R. Kavitha, T Christopher },
title = { A Study on ECG Signal Classification Techniques },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 14 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number14/15052-3398/ },
doi = { 10.5120/15052-3398 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:04:12.049091+05:30
%A R. Kavitha
%A T Christopher
%T A Study on ECG Signal Classification Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 14
%P 9-14
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The abnormal condition of the electrical activity in the heart is using electrocardiogram shows a threat to human beings. It is a representative signal containing information about the condition of the heart. The P-QRS-T wave shape, size and their time intervals between its various peaks contain useful information about the nature of disease affecting the heart. This paper presents a technique to examine electrocardiogram (ECG) signal, by taking the features form the heart beats classification. ECG Signals are collected from MIT-BIH database. The heart rate is used as the base signal from which certain parameters are extracted and presented to the network for classification. This survey provides a comprehensive overview for the classification of heart rate.

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Index Terms

Computer Science
Information Sciences

Keywords

ECG Signal MIT BIH Database PQRST Wave

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