Prediction of elbow joint movement angle based onsurface electromyography

In the development of upper limb rehabilitation treatment system,surface electromyography (sEMG),with the capacity of reflecting users' action intention,is widely used.Aiming at the problem that the arm joints of the upper limb rehabilitation robot are not flexible,this paper proposes a sEMG based elbow joint motion angle prediction method.To solve the problem that the stability of time domain feature extraction methodis insufficient,we use electromyography signal sampling analyzer and three-dimensional inertial position tracker acquire sEMG and the rotation information of the joint movement,extracting featuresfrom the time domain and frequency domain respectively,utilizing BP artificial neural network to establish the mapping relationship between sEMG and elbow angle.The experimental results show that the predictive results of this model are highly consistent with the true angle values,which is helpful to improve the flexibility of the upper limb rehabilitation manipulator