An improved incremental online training algorithm for reducing the influence of muscle fatigue in sEMG based HMI

Author

Yi Zhang ; Xinli Xu ; Yuan Luo ; Huosheng Hu ; Huiyu Zhou

Author_Institution

Res. Center of Intell. Syst. & Robot., Nat. Eng. R&D Center for Inf. Accessibility, Chongqing, China

fYear

2012

fDate

11-14 Dec. 2012

Firstpage

683

Lastpage

688

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.

Keywords

electromyography; learning (artificial intelligence); medical signal processing; signal classification; support vector machines; user interfaces; wavelet transforms; SVM; classification accuracy; continuous wavelet transform; human-machine interface; incremental online training algorithm; muscle fatigue; sEMG based HMI; sEMG classification; support vector machine; surface electromyographic signal; training speed;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Biomimetics (ROBIO), 2012 IEEE International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4673-2125-9

Type

conf

DOI

10.1109/ROBIO.2012.6491046

Filename

6491046