Brain-Computer Interfaces: Towards Practical Implementations and Potential ApplicationsView this Special Issue
Research Article | Open Access
Gerolf Vanacker, José del R. Millán, Eileen Lew, Pierre W. Ferrez, Ferran Galán Moles, Johan Philips, Hendrik Van Brussel, Marnix Nuttin, "Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving", Computational Intelligence and Neuroscience, vol. 2007, Article ID 025130, 12 pages, 2007. https://doi.org/10.1155/2007/25130
Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving
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.
- J. d. R. Millán, F. Renkens, J. Mouriño, and W. Gerstner, “Noninvasive brain-actuated control of a mobile robot by human EEG,” IEEE Transactions on Biomedical Engineering, vol. 51, no. 6, pp. 1026–1033, 2004.
- J. d. R. Millán, “Brain-computer interfaces,” in Handbook of Brain Theory and Neural Networks, M. A. Arbib, Ed., pp. 178–181, MIT Press, Cambridge, Mass,USA, 2002.
- J. d. R. Millán, F. Renkens, J. Mouriño, and W. Gerstner, “Brain-actuated interaction,” Artificial Intelligence, vol. 159, no. 1-2, pp. 241–259, 2004.
- M. Nuttin, D. Vanhooydonck, E. Demeester, and H. Van Brussel, “Selection of suitable human-robot interaction techniques for intelligent wheelchairs,” in Proceedings of the 11th IEEE International Workshop on Robot and Human Interactive Communication (ROMAN '02), pp. 146–151, Berlin, Germany, September 2002.
- G. Vanacker, D. Vanhooydonck, E. Demeester et al., “Adaptive filtering approach to improve wheelchair driving performance,” in Proceedings of the 15th IEEE International Symposium on Robot and Human Interactive Communication (ROMAN '06), pp. 527–532, Hatfield, UK, September 2006.
- D. Vanhooydonck, E. Demeester, M. Nuttin, and H. Van Brussel, “Shared control for intelligent wheelchairs: an implicit estimation of the user intention,” in Proceedings of the 1st International Workshop on Advances in Service Robotics (ASER '03), pp. 176–182, Bardolino, Italy, March 2003.
- E. Demeester, M. Nuttin, D. Vanhooydonck, and H. Van Brussel, “A model-based, probabilistic framework for plan recognition in shared wheelchair control: experiments and evaluation,” in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '03), vol. 2, pp. 1456–1461, Las Vegas, Nev, USA, October 2003.
- N. I. Katevas, N. M. Sgours, S. G. Tzafestas et al., “The autonomous mobile robot SENARIO: a sensor-aided intelligent navigation system for powered wheelchairs,” IEEE Robotics & Automation Magazine, vol. 4, no. 4, pp. 60–70, 1997.
- E. Prassler, J. Scholz, and M. Strobel, “MAid: mobility assistance for elderly and disabled people,” in Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (IECON '98), vol. 4, pp. 2493–2498, Aachen, Germany, August-September 1998.
- H. Yanco, Shared user-computer control of a robotic wheelchair system, Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, Mass, USA, September 2000.
- G. Bourhis, O. Horn, O. Habert, and A. Pruski, “An autonomous vehicle for people with motor disabilities,” IEEE Robotics & Automation Magazine, vol. 8, no. 1, pp. 20–28, 2001.
- R. S. Rao, K. Conn, S. H. Jung et al., “Human robot interaction: application to smart wheelchairs,” in Proceedings of IEEE International Conference on Robotics and Automation (ICRA '02), vol. 4, pp. 3583–3588, Washington, DC, USA, May 2002.
- R. C. Simpson, S. P. Levine, D. A. Bell, L. A. Jaros, Y. Koren, and J. Borenstein, “NavChair: an assistive wheelchair navigation system with automatic adaptation,” in Proceedings of the Assistive Technology and Artificial Intelligence, Applications in Robotics, User Interfaces and Natural Language Processing, vol. 1458 of Lecture Notes in Computer Science, pp. 235–255, 1998.
- T. Röfer and A. Lankenau, “Architecture and applications of the Bremen autonomous wheelchair,” in Proceedings of the 4th Joint Conference on Information Systems, vol. 1, pp. 365–368, Association for Intelligent Machinery, October 1998.
- L. I. Kuncheva, Combining Pattern Classifiers: Methods and Algorithms, John Wiley & Sons, New York, NY, USA, 2004.
- A. Buttfield, P. W. Ferrez, and J. d. R. Millán, “Towards a robust BCI: error potentials and online learning,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 14, no. 2, pp. 164–168, 2006.
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.