Abstract
Recording of Electrocardiogram (ECG) signal is a non-invasive method for examining the electrical actions of the heart. The characterization of ECG beat is an important step in finding the location of various heart ailments. The abnormal beats are the symptoms of several diseases such as myocardial infarction and ischemic heart diseases. The classification of beats in healthy and diseased subjects aids the researchers to detect various abnormalities in case of any arrhythmia. The arrhythmias of heart like structural, circulatory or electrical can be diagnosed by classifying the abnormal beats. Thus, the classification of ECG beats is necessary in detecting and diagnosing the diseases. In this paper, the computational methodologies adopted for ECG beat classification and the issues related to it are presented. Further, the feature extraction and feature classification methods of ECG signal have been reviewed.
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