Surface electromyography disposal based on the method of wavelet de-noising and power spectrum

While Suriace Electromyography (SEMG) using traditional disposal, the individual difierence is obvious. In order to reduce these disadvantages, SEMG signal k predisposed by wavelet de-noising theory. After the signal is decomposed and reconstructed by wavelet functious, noise is eliminated, and then, uslng Power Spectrum Coefiicients (PSC) method to analyze it By calculated the parameters of power spectrum, we got the ratio ef power spectrum and knew the relations between hand movement and power spectrum. This method is suitable for the ieature extraction of nonspecific person's SEMG. The result of experimentation shows that recognition of hand movement is me& better an the method only ming PSC. At the same time, adopt virtual instrument technology to raise accuracy of measurement and to reduce the cost