Control method for exoskeleton ankle with surface electromyography signals

被引:3
作者
张震 [1 ]
王震 [1 ]
蒋佳芯 [1 ]
钱晋武 [1 ]
机构
[1] School of Mechatronics Engineering and Automation, Shanghai University
关键词
electromyography(EMG); exoskeleton ankle; neural network; control method;
D O I
暂无
中图分类号
R318.0 [一般性问题];
学科分类号
0831 ;
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.
引用
收藏
页码:270 / 273
页数:4
相关论文
共 2 条
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Dynamic muscle force predictions from EMG: an artificial neural network approach[J] . Ming Ming Liu,Walter Herzog,Hans H.C.M. Savelberg.Journal of Electromyography and Kinesiology . 1999 (6)
[2]   An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo [J].
Lloyd, DG ;
Besier, TF .
JOURNAL OF BIOMECHANICS, 2003, 36 (06) :765-776