Tsui, Chun Sing Louis and Gan, John Q and Hu, Huosheng (2011) A Self-Paced Motor Imagery Based Brain-Computer Interface for Robotic Wheelchair Control. Clinical EEG and Neuroscience, 42 (4). pp. 225-229. DOI https://doi.org/10.1177/155005941104200407
Tsui, Chun Sing Louis and Gan, John Q and Hu, Huosheng (2011) A Self-Paced Motor Imagery Based Brain-Computer Interface for Robotic Wheelchair Control. Clinical EEG and Neuroscience, 42 (4). pp. 225-229. DOI https://doi.org/10.1177/155005941104200407
Tsui, Chun Sing Louis and Gan, John Q and Hu, Huosheng (2011) A Self-Paced Motor Imagery Based Brain-Computer Interface for Robotic Wheelchair Control. Clinical EEG and Neuroscience, 42 (4). pp. 225-229. DOI https://doi.org/10.1177/155005941104200407
Abstract
<jats:p> 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. </jats:p>
Item Type: | Article |
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Uncontrolled Keywords: | Brain-Computer Interface; Electroencephalography, Signals; Online Practice; Wheelchair Control, Robotic |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 22 Mar 2013 22:18 |
Last Modified: | 30 Oct 2024 19:44 |
URI: | http://repository.essex.ac.uk/id/eprint/5903 |