Analysis of Biological Signals Using Wavelet Coefficients for Finding the Cardiac Diseases & Their Severity

Our paper deals with feature extraction of Bio Medical signals using the continuous wavelet transform CWT and corresponding coefficients. We analyze the signal features, in various points of time and at different localization levels with multiple scales of the cwt. In this paper we have analyzed the digital data collected using the electrocardiogram for finding the heart disease considering data sets of twenty different disease cases using mat lab. Firstly we have filtered the ecg data for hum noise and muscle noise, using a series of filters and applied the zero cross algorithm for finding the no of zero crossings and the heart rate of each disease case. We have applied wavelet transform and found the wavelet 3D plot which is the representation of the wavelet coefficients, which helps for estimating the cardiac disease from the wavelet 3D plot of the patient’s electrocardiogram.