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Context-based Filtering for Assisted Brain-Actuated Wheelchair Driving
Type of publication: Journal paper
Citation: millan:2007:cin-wheelchair
Journal: Computational Intelligence and Neuroscience
Volume: 2007
Year: 2007
Abstract: Controlling a robotic device by using human brain signals is an interesting and challenging task. The device may be complicated to control and the non-stationary nature of the brain signals provides for a rather unstable input. With the use of intelligent processing algorithms adapted to the task at hand however, the performance can be increased. This paper introduces a shared control system that helps the subject in driving an intelligent wheelchair with a non-invasive brain interface. The subject's steering intentions are estimated from electroencephalogram (EEG) signals and passed through to the shared control system before being sent to the wheelchair motors. Experimental results show a possibility for significant improvement in the overall driving performance when using the shared control system compared to driving without it. These results have been obtained with 2 healthy subjects during their first day of training with the brain-actuated wheelchair.
Userfields: ipdmembership={learning},
Projects Idiap
Authors Vanacker, G.
Millán, José del R.
Lew, Eileen
Ferrez, Pierre W.
Galán, Ferran
Philips, Johan
Van Brussel, H.
Nuttin, Marnix
Added by: [UNK]
Total mark: 0
  • millan_2007_cin-wheelchair.pdf