A novel RBF neural network based recognition of human upper limb active motion intention

Abstract

In view of the problem of recognition of active motion intention of human upper limb, based on the EMG signal of the upper limb surface, this paper proposes a method of predicting the angle of upper limb joint based on RBF neural network. The motion intention of shoulder joint, elbow joint and wrist joint in sagittal plane of human body is predicted and recognized effectively. The simulation results show that the RBF method proposed in this paper can better predict the angle of the upper limb, and verified that the RBF neural network method proposed in this paper can improve the accuracy of the angle prediction of the upper limb joint, which lays the algorithm framework and theoretical foundation for the human-computer interaction control of the upper limb rehabilitation robot.