In this paper, a new surface electromyography (sEMG) signal decomposition method based on spatial location is proposed for the high-density sEMG signals in dynamic muscle contraction. Firstly, according to the waveform correlation of each muscle motor units (MU) in each channel, the firing times are extracted, and then the firing times are classified by the spatial location of MU. The MU firing trains are finally obtained. The simulation results show that the accuracy rate of a single MU firing train after classification is more than 91.67%. For real sEMG signals, the accuracy rate to find a same MU by the "two source" method is over (88.3 ± 2.1)%. This paper provides a new idea for dynamic sEMG signal decomposition.
Action Potentials ; Computer Simulation ; Electromyography ; Muscle Contraction ; Muscle, Skeletal