article

Characterization of ECG beats from cardiac arrhythmia using discrete cosine transform in PCA framework

Authors:

Roshan Joy Martis,

U. Rajendra Acharya,

Jasjit S. SuriAuthors Info & Claims

Knowledge-Based Systems, Volume 45

Pages 76 - 82

https://doi.org/10.1016/j.knosys.2013.02.007

Published: 01 June 2013 Publication History

Abstract

Electrocardiogram is the P-QRS-T wave representing the cardiac depolarization and re-polarization, recorded at the body surface. The subtle changes in amplitude and duration of these waves indicate various pathological conditions. It is very difficult to decipher minute changes in the ECG wave by naked eye. Hence a computer aided diagnosis tool to classify various cardiac diseases will assist the doctors in their ECG reading. In this paper, five types of ECG beats (ANSI/AAMI EC57:1998 standard) of MIT-BIH arrhythmia database were automatically classified. Our proposed methodology involves computation of Discrete Cosine Transform (DCT) coefficients from the segmented beats of ECG, which were then subjected for principal component analysis for dimensionality reduction. Then the clinically significant principal components were fed to (i) feed forward neural network, (ii) least square support vector machine with different kernel functions, and (iii) Probabilistic Neural Network (PNN) for automatic classification. We have obtained the highest average sensitivity of 98.69%, specificity of 99.91%, and classification accuracy of 99.52% with the developed knowledge based system. The developed system is clinically ready to deploy for mass screening programs.

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cover image Knowledge-Based Systems

Knowledge-Based Systems Volume 45, Issue

June, 2013

166 pages

ISSN:0950-7051

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2013.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 June 2013

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https://dl.acm.org/doi/10.1007/s11277-024-11113-3
Kıymaç EKaya Y(2023)A novel automated CNN arrhythmia classifier with memory-enhanced artificial hummingbird algorithmExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.119162213:PCOnline publication date: 1-Mar-2023
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https://dl.acm.org/doi/10.1007/s00521-023-08534-9
Patro KPrakash ASamantray SPławiak JTadeusiewicz RPławiak P(2022)A Hybrid Approach of a Deep Learning Technique for Real–Time ECG Beat DetectionInternational Journal of Applied Mathematics and Computer Science10.34768/amcs-2022-003332:3(455-465)Online publication date: 1-Sep-2022
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