Power line interference rejection from surface electromyography signal using an adaptive algorithm

This work focuses on the power line interference (PLI) rejection from surface EMG signal. It contains three parts: the algorithm, the experimental setting and the results. This study begins with describing the new technique, which consists in filtering respiratory surface electromyogram signals (EMG + PLI), then, becoming familiar with it. The proposed algorithm requires only one channel to both estimating the adaptive filter input reference noise and the EMG signal. The algorithm of PLI rejection has been organized into two steps. The first step insists to apply adaptive filter, especially the LMS one, in which the reference input is mathematically constructed using two different cosine functions; 50 Hz (the fundamental) function and 150 Hz (the first harmonic) function. Whereas, the second step applies the matching pursuit algorithm that uses the cosine packet dictionary to improve the result of PLI obtained at the first step. After trying statistical, as well as mathematical analysis, the complete investigation ensures that all details and steps make proof that our rigorous method is appropriate, we have also compared our method with the previous known techniques.