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Abnormality Detection in Indian ECG using Correlation Techniques
Author(s) -
Shahanaz Ayub,
Jyoti Saini
Publication year - 2012
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/9352-3683
Subject(s) - abnormality , computer science , correlation , artificial intelligence , pattern recognition (psychology) , medicine , mathematics , psychiatry , geometry
The paper proposes a method based on signal processing correlation technique to find out whether the ECG is normal or abnormal. Many of the abnormal ECGs are called Arrhythmias. ECG (lead II) obtained from conventional ECG machine of Indian patients are digitized and the data are crosscorrelated with the reference standard normal ECG data. Two different beats of the same ECG data are also correlated. The correlation parameters are used to identify the ECG as normal or abnormal. The accuracy obtained in this method is 100%. The cross-correlation is done using MATLAB 7.12.0 (R2011a) tools.

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