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• W4303982478 abstract "This study proposed a control method, a data-driven predictive control (DDPC), for the hand exoskeleton used for active, passive, and resistive rehabilitation. DDPC is a model-free approach based on past system data. One of the strengths of DDPC is that constraints of states can be added to the controller while performing the controller design. These features of the control algorithm eliminate an essential problem for rehabilitation robots in terms of easy customization and safe repetitive rehabilitation tasks that can be planned within certain constraints. Experiments were carried out with a designed hand rehabilitation system under repetitive and various therapy tasks. Real-time experiment results demonstrate the feasibility and efficiency of the proposed control approach to rehabilitation systems." @default.
• W4303982478 created "2022-10-10" @default.
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• W4303982478 date "2022-10-09" @default.
• W4303982478 modified "2023-10-14" @default.
• W4303982478 title "Data-Driven Predictive Control of Exoskeleton for Hand Rehabilitation with Subspace Identification" @default.
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• W4303982478 doi "https://doi.org/10.3390/s22197645" @default.
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