Abstract
A brain machine interface (BMI) design for controlling the navigation of a power wheelchair is proposed. Real-time experiments with four able bodied subjects are carried out using the BMI-controlled wheelchair. The BMI is based on only two electrodes and operated by motor imagery of four states. A recurrent neural classifier is proposed for the classification of the four mental states. The real-time experiment results of four subjects are reported and problems emerging from asynchronous control are discussed.
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Hema, C.R., Paulraj, M.P., Yaacob, S., Adom, A.H., Nagarajan, R. (2011). Asynchronous Brain Machine Interface-Based Control of a Wheelchair. In: Arabnia, H., Tran, QN. (eds) Software Tools and Algorithms for Biological Systems. Advances in Experimental Medicine and Biology, vol 696. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7046-6_57
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DOI: https://doi.org/10.1007/978-1-4419-7046-6_57
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