Robotics 2013, 2(4), 187-197; doi:10.3390/robotics2040187
Article

Robust Bio-Signal Based Control of an Intelligent Wheelchair

1,* email, 2email, 2email and 1email
Received: 5 August 2013; in revised form: 23 September 2013 / Accepted: 25 September 2013 / Published: 30 September 2013
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.

AMA Style

Xu X, Zhang Y, Luo Y, Chen D. Robust Bio-Signal Based Control of an Intelligent Wheelchair. Robotics. 2013; 2(4):187-197.

Chicago/Turabian Style

Xu, Xiaodong; Zhang, Yi; Luo, Yuan; Chen, Dongyi. 2013. "Robust Bio-Signal Based Control of an Intelligent Wheelchair." Robotics 2, no. 4: 187-197.

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