A Method to Control Ankle Exoskeleton with Surface Electromyography Signals

This paper is concerned with a control method of an ankle exoskeleton with electromyographic(EMG) signals. The EMG signals of human ankle and the ankle exoskeleton are introduced first. Next a control method is proposed to control the ankle exoskeleton using EMG signals. The feed-forward neural network model applied here is composed of four layers and uses the back-propagation training algorithm. The output signals from neural network are processed by wavelet transform. At last, the control orders generated from the output signals are passed to the motor controller and drive the exoskeleton to move. Through experiment, the equality of neural network prediction of ankle movement is evaluated by correlation coefficient. It is shown from the experiment results that the proposed method can accurately control the movement of ankle joint.