Abstract
The article considers the robotic arm rehabilitation device for severely paralyzed and motor disabled people with a control system using a portable eye tracker and functional near-infrared spectroscopy (fNIRS). An eye tracker is used to control the trajectory of the robotic arm's grip, while fNIRS is used to switch between control planes, or to open and close a prosthetic hand. Artificial neural networks (ANN) are employed for pattern recognition in the processing of fNIRS signals. User safety is ensured by a vision system and mechanical safety elements. The pilot experiment showed the feasibility of the implemented device. A prototype of the robotic arm rehabilitation device with a spherical coordinate system was implemented to help severely paralyzed people to take care of themselves.
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Research is supported by the RFBR grant 20–08-01178.
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Afonin, A.N., Asadullayev, R.G., Sitnikova, M.A., Shamrayev, A.A. (2021). A Rehabilitation Device for Paralyzed Disabled People Based on an Eye Tracker and fNIRS. In: Kryzhanovsky, B., Dunin-Barkowski, W., Redko, V., Tiumentsev, Y. (eds) Advances in Neural Computation, Machine Learning, and Cognitive Research IV. NEUROINFORMATICS 2020. Studies in Computational Intelligence, vol 925. Springer, Cham. https://doi.org/10.1007/978-3-030-60577-3_7
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