Application of Improved Wavelet Threshold Method in SEMG De-Noising Processing

Abstract

The surface electromyography signal is often submerged by the noise background while being gathered and recorded. To some extent, the useful signal and noise signal can be separated by applying the wavelet de-noising method effectively to eliminate the noisy signal. However, there are discontinuous points and constant deviations in the traditional wavelet threshold methods. Taking these problems into consideration, the improved threshold method is proposed and based on soft threshold function to use a transition of the nonlinear function to deal with the threshold function and de-noise the SEMG. Experimental results show that the improved threshold method has better de-noising effect and higher signal-noise ratio than the traditional threshold method.