Adaptive Filtration Techniques for Impulsive Noise Removal from ECG

The electrocardiogram is most important in diagnosis and prognosis of heart disorders. It is also used to analyze different parameters related to heart. Noise in ECG can mislead us to wrong diagnosis or analysis. There are different types of noise present in ECG signal among which baseline wander and high frequency noises can be filtered by implementing fixed filters, but for impulsive noises we need an adaptive filtering technique because of their unknown characteristics. In this paper two algorithms, i.e. LMS, RLS are implemented and compared to remove EMG based impulsive noise from ECG signal. Comparison results that the RLS algorithm produces stable ECG, better convergence and better SNR improvement than LMS algorithm.