Power line noise elimination from EMG signals using adaptive Laguerre filter with fuzzy step size

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 adaptive Laguerre filter with fuzzy step size is proposed to eliminate the PLI from Electromyography (EMG) signals. The proposed Laguerre filter has the benefits of both FIR and IIR filters and can solve their limitations in noise elimination. The proposed algorithm uses an internal mathematically constructed reference noise for the adaptive Laguerre filter, thus it is independent of the power line information to eliminate the noise. This novel adaptive structure uses the Least Mean Square (LMS) method to update its weights while a Fuzzy System (FS) is used for choosing the step size of LMS method. Our practical experiments showed that our Laguerre structure with fuzzy step size could eliminate the PLI of EMG signals successfully and it was more effective than other adaptive algorithms.