A Control of Electric Wheelchair Using an EMG Based on Degree of Muscular Activity

In this paper, a control system of an electric wheelchair (EWC) using a surface electromyogram (SEMG) based on degree of muscular activity is discussed for disabled persons such as those who have spinal cord injury. The control device is attached to a joy-stick of the ready-made EWC and controls the joy-stick by motor drive. The surface electromyograms (SEMGs) of four muscles, which are the neck, both sides of shoulder and the cheek, are measured, and the EWC is navigated based on the SEMG of the user. By identifying the SEMGs, seven patterns of the navigation of the EWC are possible, which are stop, advance, back, right turn, left turn, right back turn, and left back turn. Thus, users can navigate the EWC by their own intention without using their hands. In addition, this study focused on the four motions, which are right turn, left turn, right back turn, and left back turn. For these motions, two new methods to determine the target angle of the joy-stick based on both the degree and duration of the muscular activity during straining the corresponding muscle are proposed. In order to verify the maneuverability of the EWC by the proposed two methods, run experiments in two test courses were carried out, and results were compared with the conventional method.

[1]  Kazuo Tanaka,et al.  Electroencephalogram-based control of an electric wheelchair , 2005, IEEE Transactions on Robotics.

[2]  Youngjin Choi,et al.  EMG-based continuous control method for electric wheelchair , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Nguyen Truong-Thinh,et al.  Using Electrooculogram and Electromyogram for powered wheelchair , 2011, 2011 IEEE International Conference on Robotics and Biomimetics.

[4]  Guanglin Li,et al.  Hybrid brain/muscle-actuated control of an intelligent wheelchair , 2013, 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[5]  Kazuhiko Takahashi,et al.  Wheelchair control using an EOG- and EMG-based gesture interface , 2009, 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[6]  Huosheng Hu,et al.  EMG-based hands-free wheelchair control with EOG attention shift detection , 2007, 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[7]  Dongyi Chen,et al.  Robust Bio-Signal Based Control of an Intelligent Wheelchair , 2013, Robotics.

[8]  Huosheng Hu,et al.  Design of a surface EMG based human-machine interface for an intelligent wheelchair , 2011, IEEE 2011 10th International Conference on Electronic Measurement & Instruments.

[9]  Rampriya Mahendran,et al.  EMG signal based control of an intelligent wheelchair , 2014, 2014 International Conference on Communication and Signal Processing.