Adaptive Powerline Interference Removal from Cardiac Signals Using Leaky Based Normalized Higher Order Filtering Techniques

In this paper we present an adaptive filter for denoising the ECG signal based on Least Mean Fourth (LMF) algorithms. LMF algorithm exhibits lower steady state error than the conventional LMS algorithm. This is due to the fact that the excess mean-square error of the LMS algorithm is dependent only on the second order moment of the noise. The second order moment, or variance of the noise evaluates to be the same for all the noise environments. Based upon this other types of mean fourth based algorithms are implemented. These are Normalized LMF (NLMF) and Error Normalized LMF (ENLMF). In order to increase the stability of the filter leakage factor is introduced. Based on these considerations Normalized Leaky LMF (NLLMF) and Error Normalized Leaky LMF (ENLLMF) adaptive cancellers are developed for cardiac signal enhancement. Different filter structures are presented to eliminate the 60 Hz power line interference from the ECG signal. Finally, we have applied this algorithm on ECG signals from the MIT-BIH data base and compared its performance with the conventional LMS algorithm. The results show that the performance of the ENLLMF based noise reduction filter is superior than the other implementations in terms of signal to noise ratio increment.