A study on surface EMG generation model and its extraction

A surface electromyography (sEMG) signal model is established and extracted from noisy background. Firstly, single fiber action potential (SFAP), motor unit action potential (MUAP) and motor unit action potential train (MUAPT) are simulated based on the tripolar signal source model, and then the sEMG is obtained. Secondly, the simulated sEMG signal is extracted from the mixed signals that consists of white noises, power frequency interference signal and electrocardio signal by independent component analysis (ICA) algorithms, and the most effective signal decomposition method Informax is chosen. It will lay the foundation for further decomposing the signals into single MUAP.