Power Line Noise Elimination from EMG Signals Using Adaptive Laguerre Filter with Fuzzy Step Size

Power Line Noise Elimination from EMG Signals Using Adaptive Laguerre Filter with Fuzzy Step Size

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Part of #Power Line Noise Elimination from EMG Signals Using Adaptive Laguerre Filter with Fuzzy Step Size# :

Publishing year : 2010

Conference : 17th Iranian Conference on Medical Engineering

Number of pages : 4

Abstract: Biomedical signals are always corrupt with different noise and interferences. Power Line Interference (PLI) is one of the most important interferences that significantly reduces the quality of biomedical signals. 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 an 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 the Fuzzy System (FS) is used to select the step size of the LMS method. Our practical experiments showed that our Laguerre structure with fuzzy step size could successfully eliminate the PLI of EMG signals and was more effective than other adaptive algorithms.