Upper limb electrical stimulation using input-output linearization and iterative learning control
Upper limb electrical stimulation using input-output linearization and iterative learning control
A control scheme is developed for multi-joint upper limb reference tracking using functional electrical stimulation (FES). In accordance with the needs of stroke rehabilitation, FES is applied to a reduced set of muscles in the arm and shoulder, with support against gravity provided by a passive exoskeletal mechanism. The approach fuses input-output linearization with iterative learning control (ILC), one of the few techniques to have been applied in clinical treatment trials with patients. This powerful hybrid control structure hence extends performance and scope of clinically proven technology for widespread application in rehabilitation robotic and FES domains. In addition to simplifying tracking and convergence properties of the stimulated joints, the framework enables conditions for the stability of unstimulated joints to be derived for the first time. Experimental results confirm tracking performance of the stimulated joints, together with unstimulated joint stability.
1546-1554
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
18 January 2015
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Freeman, C.T.
(2015)
Upper limb electrical stimulation using input-output linearization and iterative learning control.
IEEE Transactions on Control Systems Technology, 23 (4), .
(doi:10.1109/TCST.2014.2363412).
Abstract
A control scheme is developed for multi-joint upper limb reference tracking using functional electrical stimulation (FES). In accordance with the needs of stroke rehabilitation, FES is applied to a reduced set of muscles in the arm and shoulder, with support against gravity provided by a passive exoskeletal mechanism. The approach fuses input-output linearization with iterative learning control (ILC), one of the few techniques to have been applied in clinical treatment trials with patients. This powerful hybrid control structure hence extends performance and scope of clinically proven technology for widespread application in rehabilitation robotic and FES domains. In addition to simplifying tracking and convergence properties of the stimulated joints, the framework enables conditions for the stability of unstimulated joints to be derived for the first time. Experimental results confirm tracking performance of the stimulated joints, together with unstimulated joint stability.
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Published date: 18 January 2015
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EEE
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Local EPrints ID: 361358
URI: http://eprints.soton.ac.uk/id/eprint/361358
ISSN: 1063-6536
PURE UUID: 0346cda4-9f10-42a4-9430-c672658ff7db
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Date deposited: 18 Jan 2014 14:49
Last modified: 14 Mar 2024 15:49
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C.T. Freeman
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