Simulation of surface electromyography signal acquisition and extraction of badminton players
In order to more accurately analyze the movement details of the upper limbs of badminton play-ers,this paper proposes a collection and extraction method based on surface EMG signals.Different EMG signals are collected to reflect the action state,local action feature vectors of the upper limbs are extracted,and wavelet transform combined with adaptive filtering is used to preprocess the surface EMG signals corre-sponding to different actions collected in the experiment to obtain pure surface EMG signals.The neural network algorithm is used to compare the time-domain,frequency-domain and time-frequency characteristics of surface EMG signals on the upper limb movement of badminton players.The rationality of the upper limb movement simulation model is verified by computer simulation.The results show that the proposed method can effectively collect the laws of the upper limb movement of badminton players,with high recognition ac-curacy and high movement execution integrity.
badmintonsurface electromyographylocal movements of upper limbswavelet transformneural network algorithm
万方数据
维普
