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Developing Resource Efficient Heart Arrhythmia Classifier

by Atif Jan, Numan Khurshid, Muhammad Irfan Khattak
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 109 - Number 16
Year of Publication: 2015
Authors: Atif Jan, Numan Khurshid, Muhammad Irfan Khattak
10.5120/19274-1014

Atif Jan, Numan Khurshid, Muhammad Irfan Khattak . Developing Resource Efficient Heart Arrhythmia Classifier. International Journal of Computer Applications. 109, 16 ( January 2015), 35-39. DOI=10.5120/19274-1014

@article{ 10.5120/19274-1014,
author = { Atif Jan, Numan Khurshid, Muhammad Irfan Khattak },
title = { Developing Resource Efficient Heart Arrhythmia Classifier },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 109 },
number = { 16 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume109/number16/19274-1014/ },
doi = { 10.5120/19274-1014 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:44:58.690373+05:30
%A Atif Jan
%A Numan Khurshid
%A Muhammad Irfan Khattak
%T Developing Resource Efficient Heart Arrhythmia Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 109
%N 16
%P 35-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents development of optimal digital circuit for the Heart Disease Classification using Cartesian Genetic Programming (CGP) for different types of arrhythmia. Extensive research work has already been carried out in this domain but non-linear nature of the technique remained one of the hurdles in its hardware prototyping. Efficient circuit development for resource constraint environment of the classifier remained an unsolved problem due to its algorithmic complexity. CGP system is trained to generate a classifier circuit based upon the fiducial points extracted out of the Electrocardiography (ECG) signals of dataset. Experimental results reported on heart disease data from machine learning repository of MIT-BIH showed satisfactory results as compare to other contemporary methods used in the field.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Cartesian Genetic Programming Neuro-evolution CVD Cardiac Arrhythmias Classification Fiducial points LBBB beats RBBB beats.

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