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Multiple model adaptive control of functional electrical stimulation

Multiple model adaptive control of functional electrical stimulation
Multiple model adaptive control of functional electrical stimulation
This paper establishes the feasibility of multiple-model switched adaptive control to regulate functional electrical stimulation for upper limb stroke rehabilitation. An estimation-based multiple-model switched adaptive control (EMMSAC) framework for nonlinear time-invariant systems is described, and extensions are presented to enable application to time-varying Hammerstein structures that can accurately represent the stimulated arm. A principled design procedure is then developed to construct both a suitable set of candidate models from experimental data and a corresponding set of tracking controllers. The procedure is applied to a sample of able-bodied young participants to produce a general EMMSAC controller. This is then applied to a different sample of the population during an isometric nonvoluntary trajectory tracking task. The results show that it is possible to eliminate model identification while employing closed-loop controllers that maintain high performance in the presence of rapidly changing system dynamics. This paper hence addresses critical limitations to effective stroke rehabilitation in a clinical setting.
1063-6536
1901-1913
Brend, O.
0932d595-1da7-4a16-8e7e-2d065a058866
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
French, M.
22958f0e-d779-4999-adf6-2711e2d910f8
Brend, O.
0932d595-1da7-4a16-8e7e-2d065a058866
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
French, M.
22958f0e-d779-4999-adf6-2711e2d910f8

Brend, O., Freeman, C.T. and French, M. (2015) Multiple model adaptive control of functional electrical stimulation. IEEE Transactions on Control Systems Technology, 23 (5), 1901-1913. (doi:10.1109/TCST.2015.2394508).

Record type: Article

Abstract

This paper establishes the feasibility of multiple-model switched adaptive control to regulate functional electrical stimulation for upper limb stroke rehabilitation. An estimation-based multiple-model switched adaptive control (EMMSAC) framework for nonlinear time-invariant systems is described, and extensions are presented to enable application to time-varying Hammerstein structures that can accurately represent the stimulated arm. A principled design procedure is then developed to construct both a suitable set of candidate models from experimental data and a corresponding set of tracking controllers. The procedure is applied to a sample of able-bodied young participants to produce a general EMMSAC controller. This is then applied to a different sample of the population during an isometric nonvoluntary trajectory tracking task. The results show that it is possible to eliminate model identification while employing closed-loop controllers that maintain high performance in the presence of rapidly changing system dynamics. This paper hence addresses critical limitations to effective stroke rehabilitation in a clinical setting.

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e-pub ahead of print date: 20 May 2015
Published date: September 2015
Organisations: Vision, Learning and Control, EEE

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Local EPrints ID: 361362
URI: http://eprints.soton.ac.uk/id/eprint/361362
ISSN: 1063-6536
PURE UUID: 3f0f218b-d6d4-48c9-891e-6b5e6c02d474

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Date deposited: 18 Jan 2014 15:35
Last modified: 15 Feb 2021 17:32

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