title: Context-based filtering for assisted brain-actuated wheelchair driving.
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 nonstationary 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 noninvasive 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.
authors: The Department of Mechanical Engineering, Katholieke Universiteit, 3001 Leuven, Belgium. gerolf.vanacker@mech.kuleuven.be
authors: Gerolf
authors: G
authors: Vanacker
authors: José
authors: J
authors: del R Millán
authors: Eileen
authors: E
authors: Lew
authors: Pierre W
authors: PW
authors: Ferrez
authors: Ferran Galán
authors: FG
authors: Moles
authors: Johan
authors: J
authors: Philips
authors: Hendrik
authors: H
authors: Van Brussel
authors: Marnix
authors: M
authors: Nuttin