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Novel Approach of Stationary & Non Stationary Implementation of NLMS & RLMS Algorithms for Suppression of Noise in Cardiac Signals

Adaptive filter is an efficient method to filter ECG signal, because it does not need the signal statistical characteristics. In this paper we present a Gaussian & novel adaptive filter for removing the Baseline wander & power line interference from ECG signals based on recursive least mean square (RLMS) algorithm & Normalized least mean square (NLMS) algorithm. These algorithms are derived based on the minimization of mean square error, average power, power spectral density (PSD). The adaptive filter essentially minimizes the mean square error between a primary input, which is a noisy ECG, and a reference input which is either noise that is correlated in some way with the noise in the primary input. Finally, we have applied RLMS algorithm on ECG signals from the MIT-BIH database and compared its performance with the NLMS algorithm. The simulation result shows that the performance of the RLMS algorithm is superior to that of the NLMS based algorithm in noise reduction.