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Research Journal of Pharmacy and Technology
Year : 2017, Volume : 10, Issue : 11
First page : ( 4116) Last page : ( 4118)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2017.00749.1

ECG signal classification based on temporal and spectral features using SVM classifier

Ali A. Mohamed Syed

AMET Business School, AMET University, Chennai

Online published on 26 March, 2018.

Abstract

An electronic device known as the Electrocardiogram (ECG) is used in monitoring the health conditions of the heart rate. As there is the increase in some heart patients all around the world, there is the need for the development of an automatic system for detecting the various abnormalities or arrhythmias of the heart. For this purpose, a new technique is proposed for the ECG signal classification system. The system is based on the temporal and spectral feature extraction from Empirical Mode Decomposition (EMD), and the performance calculation of the proposed system is done by the Support Vector Machine (SVM) based classifier. The system is mainly based on the classification of the arrhythmia disease.

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Keywords

Electrocardiogram, signal classification, EMD, SVM, arrhythmia.

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