Design of Lead II ECG Waveform and Classification Performance for Morphological features using Different Classifiers on Lead II

Abstract

The aim of thispaper is hardware optimization of the electronic circuit of electrocardiogram (ECG) by using a bio-potential amplifier in such a manner that it reduces noise, RF interference, DC offset value, and common voltage from the existing circuit.We have also made a CAD system which helps the doctor in analyzing whether patient waveform is normal or abnormal. We have used the knowledge of automatic classification of ECG signals with feature selection and extraction techniques.83 samples of 12 lead systems were collected from various doctors out of whom we have used the lead 2 samples of the ECG waveforms. In this paper, we have accurately classified and differentiated normal and abnormal waveforms. Experiments reveal that the overall classification accuracy is 71.43% using SSVM classifier.