Abstract
Robotic devices are particularly useful applications in the field of functional rehabilitation following neurological injury such as the spinal cord and stroke which lead to motor impairments. Different rehabilitation devices members are under study to assist therapists in their work. In this paper we propose to reproduce human walking movements on a robotic rehabilitation chair of lower limbs, produced in the laboratory (LRPE). To do, we apply real walking signals on developed control law for this purpose. This law using kinematic model based on neural networks {Feed forward neural network (FFNN). Reproduction actual walking movement made from OpenSim database, is open-source software allows users to that develop, analyze, and visualize models of the musculoskeletal system, to generate dynamic simulations of movement, and compare with data base’s movement. Proposed control law provides a high performance and fast convergence with extremely low error, and offers optimal reproduction of movement during human walking, and a secure rehabilitation.
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Mamou, M.A., Saadia, N. (2015). Robotic Rehabilitation of Lower Limbs “Reproduction of Human Physiological Movements”. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9141. Springer, Cham. https://doi.org/10.1007/978-3-319-20472-7_19
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DOI: https://doi.org/10.1007/978-3-319-20472-7_19
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