An Application of PCA in ECG Classification with Cross - Validation

Authors

  • Nikhil G Kurup  Lecturer, NSS Polytechnic College, Pandalam, Kerala, India

Keywords:

QRS detection; SVM; PCA ; Cross validation

Abstract

Electrocardiogram (ECG)is a non-invasive technique used mainly as a primary diagnostic tool for cardiovascular diseases. A pure ECG signal provides valuable information about the electrophysiology of heart diseases and the occurrence of ischemic changes. It provides necessary information about the functional aspects of the heart and cardiovascular system. The objective of this report is to automatically detect the cardiac problems in ECG signal. Recently developed digital signal processing and pattern recognition technique is used in this report for the detection of cardiac problems. The detection of cardiac abnormalities in ECG signal consists of following steps :detection of QRS complex in ECG signal: feature extraction from detected QRS complexes : classi?cation of beats using extracted feature set from QRS complexes. Automatic classi?cation of heart beats in turn represents the automatic detection of cardiac problems in ECG signal. Hence this report develops an automatic algorithm for classi?cation of heartbeats to detect cardiac abnormalities in ECG signals. SVM is used as a classifier and PCA is used for feature reduction. Also compared the result with out using PCA . Leave one out cross validation is also done.

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International Journal of Scientific Research in Science and Technology

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Published

2017-12-31

Issue

Volume 3, Issue 8, November-December-2017

Section

Research Articles

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How to Cite

[1]
Nikhil G Kurup, " An Application of PCA in ECG Classification with Cross - Validation, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 8, pp.394-398, November-December-2017.