Comparative Analysis of Filtering Techniques for Impulsive Noise Cancellation from Real-Time Bio-medical Signal

Impulsive Noise Cancellation in practice is a challenging task. In case of biomedical signals like ECG, EMG, EEG are even challenging for noise cancellation. These signals suffer from impulsive noise at the time of acquisition. In this paper, Cardiac signal corrupted with impulsive noise at the time of acquisition is considered. Different filtering algorithms are being applied to remove the noise. Initially the filters like FIR and two types of IIR filters are used for comparison. Further it has been proposed for adaptive filter with different Least Mean Square (LMS) algorithms. The signal has been tested and verified. Finally, the Wilcoxon norm based LMS is chosen which has an attractive result. For all the filtering techniques the signal is applied and their results are compared and are shown in result section. It shows that the proposed algorithm works better than the existing ones.