A self-paced motor imagery based brain-computer interface for robotic wheelchair control.
This paper presents a simple self-paced motor imagery based brain-computer interface (BCI) to control a robotic wheelchair. An innovative control protocol is proposed to enable a 2-class self-paced BCI for wheelchair control, in which the user makes path planning and fully controls the wheelchair except for the automatic obstacle avoidance based on a laser range finder when necessary. In order for the users to train their motor imagery control online safely and easily, simulated robot navigation in a specially designed environment was developed. This allowed the users to practice motor imagery control with the core self-paced BCI system in a simulated scenario before controlling the wheelchair. The self-paced BCI can then be applied to control a real robotic wheelchair using a protocol similar to that controlling the simulated robot. Our emphasis is on allowing more potential users to use the BCI controlled wheelchair with minimal training; a simple 2-class self paced system is adequate with the novel control protocol, resulting in a better transition from offline training to online control. Experimental results have demonstrated the usefulness of the online practice under the simulated scenario, and the effectiveness of the proposed self-paced BCI for robotic wheelchair control.
Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, United Kingdom. chun_sing_tsui@hotmail.com
Chun Sing Louis
CS
Tsui
John Q
JQ
Gan
Huosheng
H
Hu
D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D005246:Feedback; D006801:Humans; D007092:Imagination / Q000502:physiology*; D008328:Man-Machine Systems; D012371:Robotics; D014584:User-Computer Interface; D014910:Wheelchairs