Research Journal of Pharmacy and Technology
Year : 2017, Volume : 10, Issue : 12
First page : ( 4365) Last page : ( 4367)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2017.00802.2

Pan Tompkins Algorithm based ECG Signal Classification

Ali A. Mohamed Syed

Research Associate, AMET Business School, AMET University

Corresponding Author E-mail:

Online published on 26 March, 2018.

Abstract

A first diagnostic tool Electrocardiogram (ECG) is a therapeutic method used as for cardiovascular diseases. A cleaned ECG signal provides valuable information about the functional aspects of the heart and cardiovascular system. To identify the automatic detection of cardiac arrhythmias in ECG signal, a new method is proposed for the ECG signal classification based on Pan Tompkins algorithm. Using this algorithm the statistical features are extracted and by using the K Nearest Neighbor (KNN) based classifier, the performance of the proposed system can be evaluated. The method is mainly based on the arrhythmia disease classification.

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Keywords

Electrocardiogram, Pan Tompkins, classifier, statistical, arrhythmia.

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