Author(s): A. Mohamed Syed Ali

Email(s): Email ID Not Available

DOI: 10.5958/0974-360X.2017.00749.1   

Address: A. Mohamed Syed Ali
AMET Business School, AMET University, Chennai
*Corresponding Author

Published In:   Volume - 10,      Issue - 11,     Year - 2017


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.


Cite this article:
A. Mohamed Syed Ali . ECG signal classification based on temporal and spectral features using SVM classifier . Research J. Pharm. and Tech 2017; 10(11): 4116-4118. doi: 10.5958/0974-360X.2017.00749.1

Cite(Electronic):
A. Mohamed Syed Ali . ECG signal classification based on temporal and spectral features using SVM classifier . Research J. Pharm. and Tech 2017; 10(11): 4116-4118. doi: 10.5958/0974-360X.2017.00749.1   Available on: https://rjptonline.org/AbstractView.aspx?PID=2017-10-11-88


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RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 

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