Surface EMG-based human-machine interface that can minimise the influence of muscle fatigue
by Xiaodong Xu; Yi Zhang; Xinli Xu; Huosheng Hu
International Journal of Modelling, Identification and Control (IJMIC), Vol. 22, No. 4, 2014

Abstract: It is clear that the surface electromyographic-based (sEMG) human-machine interface (HMI) shows a reduction in stability when the muscle fatigue occurs. This paper presents an improved incremental training algorithm that is based on online support vector machine (SVM). The continuous wavelet transform is used to study the changes of sEMG when muscle fatigue occurs, and then the improved online SVM is applied for sEMG classification. The parameters of the SVM model are adjusted for adaptation based on the changes of sEMG signals, and the training data is conditionally selected and forgotten. Experiment results show that the presented method can perform accurate modelling and the training speed is increased. Furthermore, this method effectively overcomes the influence of muscle fatigue during a long-term operation of the sEMG-based HMI.

Online publication date: Sat, 27-Dec-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com