Paper Info
Title
Surface Emg-Based Human-Machine Interface That Can Minimise The Influence Of Muscle Fatigue
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.
Year
DOI
Venue
2014
10.1504/IJMIC.2014.066261
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL
Keywords
DocType
Volume
human-machine interface, HMI, EMG, muscle fatigue, online SVM, improved incremental training algorithm
Journal
22
Issue
ISSN
Citations 
4
1746-6172
2
PageRank 
References 
Authors
0.41
9
4
Name
Order
Citations
PageRank
Xiaodong Xu130.77
Yi Zhang241.45
Xinli Xu37910.92
Huosheng Hu42009220.95