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Publication type: Article in Proceedings
Author: C. Mandel, T. L√ľth, T. Laue, T. R√∂fer, A. Gr√§ser, B. Krieg-Br√ľckner
Editor: Ning Xi, W. R. Hamel
Title: Navigating a Smart Wheelchair with a Brain-Computer Interface Interpreting Steady-State Visual Evoked Potentials
Book / Collection title: Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
Page(s): 1118 – 1125
Year published: 2009
Publisher: IEEE
Abstract: In order to allow severely disabled people who cannot move their arms and legs to steer an automated wheelchair, this work proposes the combination of a non-invasive EEG-based human-robot interface and an autonomous navigation system that safely executes the issued commands. The robust classification of steady-state visual evoked potentials in brain activity allows for the seamless projection of qualitative directional navigation commands onto a frequently updated route graph representation of the environment. The deduced metrical target locations are navigated to by the application of an extended version of the well-established Nearness Diagram Navigation method. The applicability of the system proposed is demonstrated by a real-world pilot study in which nine untrained subjects successfully navigated an automated wheelchair, requiring only some ten minutes of preparation.
Status: Reviewed
Last updated: 23. 10. 2009

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