Paper Info
Title
An improved incremental online training algorithm for reducing the influence of muscle fatigue in sEMG based HMI
Abstract
Considering the problem that stability of surface Electromyographic Signal (sEMG) based human-machine interface (HMI) gradually declines as fatigue takes place in muscles, we propose a novel method for updating samples to improve incremental online training algorithm for support vector machine (SVM). We study the changes of sEMG when muscle fatigue occurs using a method based on continuous wavelet transform, and then applies the improved incremental online SVM for sEMG classification. Experiment results show that the proposed algorithm can be used to improve the classification accuracy and training speed significantly. Furthermore, this method effectively diminish the influence of muscle fatigue during long-term operation of sEMG based HMI.
Year
DOI
Venue
2012
10.1109/ROBIO.2012.6491046
ROBIO
Keywords
Field
DocType
semg based hmi,training speed,wavelet transforms,user interfaces,learning (artificial intelligence),human-machine interface,continuous wavelet transform,medical signal processing,svm,muscle fatigue,support vector machine,signal classification,electromyography,classification accuracy,incremental online training algorithm,support vector machines,semg classification,surface electromyographic signal
Pattern recognition,Support vector machine,Algorithm,Continuous wavelet transform,Speech recognition,Artificial intelligence,Engineering,Muscle fatigue
Conference
ISBN
Citations 
PageRank 
978-1-4673-2125-9
0
0.34
References 
Authors
7
5
Name
Order
Citations
PageRank
Yi Zhang141.45
Xinli Xu27910.92
Yuan Luo387.02
Huosheng Hu42009220.95
Huiyu Zhou51303111.91