Adaptive Laguerre Filters for Elimination of Power Line Noise from EMG Signals: Fixed and Fuzzy Step Size Approaches

Biomedical signals are always corrupted with different noises and interferences. Power Line Interference (PLI) is one of the most important interferences, which decreases the quality of the biomedical signals significantly. In this paper, a novel algorithm, based on adaptive IIR Laguerre filters has been proposed to eliminate the Power Line Interference (PLI) and its harmonics from Electromyography (EMG) signals. The proposed algorithm has used an internal mathematically constructed reference noise for the adaptive Laguerre filter, thus it is independent of the power line information to eliminate the noise. The Least Mean Square (LMS) algorithm with fuzzy step size has been used to optimize the filter weights which highly increase the filter performance. This proposed filter has consumed fewer computational load than adaptive FIR filters, and also it has shown better stability than IIR filters. Our practical experiments showed that our Laguerre structures could eliminate the PLI from EMG signals successfully and increased the SNR up to 12db that was more efficient than other adaptive algorithms.