Computational Intelligence and Neuroscience
Volume 2007 (2007), Article ID 25130, 12 pages
doi:10.1155/2007/25130
Research Article

Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving

Gerolf Vanacker,1 José del R. Millán,2 Eileen Lew,2 Pierre W. Ferrez,2 Ferran Galán Moles,2 Johan Philips,1 Hendrik Van Brussel,1 and Marnix Nuttin1

1The Department of Mechanical Engineering, Katholieke Universiteit, Leuven 3001, Belgium
2The IDIAP Research Institute, Martigny 1920, Switzerland

Received 18 February 2007; Accepted 23 May 2007

Academic Editor: Fabio Babiloni

Copyright © 2007 Gerolf Vanacker et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.