The decomposition of surface EMG signals based on blind source separation of convolved mixtures

The decomposition of surface EMG signals can provide valuable information about the recruitment and firing of motor units from surface EMG recordings. According to the physiologic characteristic of the surface EMG signals generation, a method of the decomposition of SEMG signals based on the technique of convolved mixing blind source separation was proposed. Using simulated SEMG signals, the performance of the decomposition algorithm was analyzed and compared with that of the decomposition technique adopting Independent Component Analysis (ICA). The experiment results show that the proposed method could decompose SEMG signals effectively, and it's performance is better than the ICA decomposition method, no matter for the simulated or recorded SEMG signals.