Abstract
Controlling a power wheelchair using a brain machine interface (BMI) requires sufficient subject training. A neural network based BMI design using motor imagery of four states is used to control the navigation of a power wheelchair. The online experiment results are presented for two indoor navigation protocols. Twotrained subjects participated in the study.Performance of the real-time experiments is assessed based on the targets reached, time taken to reach the targets and on completion of a given navigation protocol.A performance rate of 85.7% is achievable by both subjects for the real-time experiments.
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© 2011 Springer-Verlag Berlin Heidelberg
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Hema, C.R., Paulraj, M.P. (2011). Control Brain Machine Interface for a Power Wheelchair. In: Osman, N.A.A., Abas, W.A.B.W., Wahab, A.K.A., Ting, HN. (eds) 5th Kuala Lumpur International Conference on Biomedical Engineering 2011. IFMBE Proceedings, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21729-6_75
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DOI: https://doi.org/10.1007/978-3-642-21729-6_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21728-9
Online ISBN: 978-3-642-21729-6
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