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Robust Bio-Signal Based Control of an Intelligent Wheelchair
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Engineering Research & Development Center for Information Accessibility, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
* Author to whom correspondence should be addressed.
Received: 5 August 2013; in revised form: 23 September 2013 / Accepted: 25 September 2013 / Published: 30 September 2013
Abstract: 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.
Keywords: intelligent wheelchair; sEMG; incremental support vector machine; human-machine interaction
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MDPI and ACS Style
Xu, X.; Zhang, Y.; Luo, Y.; Chen, D. Robust Bio-Signal Based Control of an Intelligent Wheelchair. Robotics 2013, 2, 187-197.
Xu X, Zhang Y, Luo Y, Chen D. Robust Bio-Signal Based Control of an Intelligent Wheelchair. Robotics. 2013; 2(4):187-197.
Xu, Xiaodong; Zhang, Yi; Luo, Yuan; Chen, Dongyi. 2013. "Robust Bio-Signal Based Control of an Intelligent Wheelchair." Robotics 2, no. 4: 187-197.