EMG signal Analysis and Identification of Human Calf Muscles based on Walking on Different Slope Road

摘要

In order to identify the road slope by leg EMG signal, we use OpenSim to analyze the relationship between ankle movement and calf muscle length; tibialis anterior muscle and gastrocnemius muscle are selected in the EMG signal acquisition test; the EMG signals of chosen muscles are obtained when walking on seven different slope roads; BP neural network is used to identify the signal after time-domain (iEMG, VAR, and RMS) and frequency-domain(MF and MPF) feature analysis. The results show that the EMG signals of tibialis anterior muscle and gastrocnemius muscle can identify the slope of road with an average recognition rate of 87.68%. The results provide a basis for human-computer interaction technology with EMG signal as input.