Comparison of Filter Approximation Methods for ECG Filtering – As Per AHA Recommendations

Abstract

Healthcare is one of the fastest growing sectors. Physicians use various parameters from a patient to diagnose the ailment for its treatment and cure. ECG is one of the most vital parameter for monitoring and diagnosing different types of diseases and disorders related to the heart. Till now various monitoring systems have been developed for this very reason. From the background study it has been seen that each system has its own specifications. Sometimes they use only a standard single order filter approximation method. Each system has its own frequency related specifications like frequency cut off and range selection. When analysed, their output is most of the time not satisfactory. So in this thesis, various filter approximation methods have been designed using the specifications which are provided by American Heart Association (AHA); a well known and prominent organisation of scientists in USA who underlines the various specifications of designing the ECG systems. After Analysis, the 1st order High Pass filter, inverse chebyshev Low Pass Filter has been found to give better response. The Fast Fourier transform (FFT) analysis of output signals from filters have been done for feature extraction.