Robust Bio-Signal Based Control of an Intelligent Wheelchair

Robotics

Xiaodong Xu¹  Yi Zhang²  Yuan Luo² 

[1] School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; E-Mail:;Engineering Research & Development Center for Information Accessibility, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; E-Mails:

关键词: intelligent wheelchair;    sEMG;    incremental support vector machine;    human-machine interaction;   

DOI  :  10.3390/robotics2040187

来源: mdpi

【 摘 要 】

In this paper, an adaptive human-machine interaction (HMI) method that is based on surface electromyography (sEMG) signals is proposed for the hands-free control of an intelligent wheelchair. sEMG signals generated by the facial movements are obtained by a convenient dry electrodes sensing device. After the signals features are extracted from the autoregressive model, control data samples are updated and trained by an incremental online learning algorithm in real-time. Experimental results show that the proposed method can significantly improve the classification accuracy and training speed. Moreover, this method can effectively reduce the influence of muscle fatigue during a long time operation of sEMG-based HMI.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.