摘要
This paper is concerned with a control method for an exoskeleton ankle with electromyography （EMG） signals. The EMG signals of human ankle and the exoskeleton ankle are introduced. Then a control method is proposed to control the exoskeleton ankle using the 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 the wavelet transform. Finally the control orders generated from the output signals are passed to the motor controller and drive the exoskeleton to move. Through experiments, the equality of neural network prediction of ankle movement is evaluated by giving the correlation coefficient. It is shown from the experimental results that the proposed method can accurately control the movement of ankle joint.
This paper is concerned with a control method for an exoskeleton ankle with electromyography （EMG） signals. The EMG signals of human ankle and the exoskeleton ankle are introduced. Then a control method is proposed to control the exoskeleton ankle using the 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 the wavelet transform. Finally the control orders generated from the output signals are passed to the motor controller and drive the exoskeleton to move. Through experiments, the equality of neural network prediction of ankle movement is evaluated by giving the correlation coefficient. It is shown from the experimental results that the proposed method can accurately control the movement of ankle joint.
基金
supported by the National High-Tech R&D Program (Grant No.2006AA04Z224)
the Innovation Program of Shanghai Municipal Education Commission (Grant No.08ZZ48)
the Shanghai Leading Academic Discipline Project (Grant No.Y0102)
