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Identification of electrically stimulated muscle models of stroke patients

Identification of electrically stimulated muscle models of stroke patients
Identification of electrically stimulated muscle models of stroke patients
Despite significant recent interest in the identification of electrically stimulated muscle models, current methods are based on underlying models and identification techniques that make them unsuitable for use with subjects who have incomplete paralysis. One consequence of this is that very few model-based controllers have been used in clinical trials. Motivated by one case where a model-based controller has been applied to the upper limb of stroke patients, and the modeling limitations that were encountered, this paper first undertakes a review of existing modeling techniques with particular emphasis on their limitations. A Hammerstein structure, already known in this area, is then selected, and a suitable identification procedure and set of excitation inputs are developed to address these short-comings. The technique that is proposed to obtain the model parameters from measured data is a combination of two iterative schemes: the first of these has rapid convergence and is based on alternating least squares, and the second is a more complex method to further improve accuracy. Finally, experimental results are used to assess the efficacy of the overall approach.
0967-0661
396-407
Le, Fengmin
3e44aa4d-33ea-4697-a9c2-b2bff35cee3c
Markovsky, Ivan
7d632d37-2100-41be-a4ff-90b92752212c
Freeman, Christopher T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
Le, Fengmin
3e44aa4d-33ea-4697-a9c2-b2bff35cee3c
Markovsky, Ivan
7d632d37-2100-41be-a4ff-90b92752212c
Freeman, Christopher T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72

Le, Fengmin, Markovsky, Ivan, Freeman, Christopher T. and Rogers, Eric (2010) Identification of electrically stimulated muscle models of stroke patients. Control Engineering Practice, 18, 396-407.

Record type: Article

Abstract

Despite significant recent interest in the identification of electrically stimulated muscle models, current methods are based on underlying models and identification techniques that make them unsuitable for use with subjects who have incomplete paralysis. One consequence of this is that very few model-based controllers have been used in clinical trials. Motivated by one case where a model-based controller has been applied to the upper limb of stroke patients, and the modeling limitations that were encountered, this paper first undertakes a review of existing modeling techniques with particular emphasis on their limitations. A Hammerstein structure, already known in this area, is then selected, and a suitable identification procedure and set of excitation inputs are developed to address these short-comings. The technique that is proposed to obtain the model parameters from measured data is a combination of two iterative schemes: the first of these has rapid convergence and is based on alternating least squares, and the second is a more complex method to further improve accuracy. Finally, experimental results are used to assess the efficacy of the overall approach.

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Submitted date: 6 January 2010
Published date: 15 January 2010
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 268356
URI: http://eprints.soton.ac.uk/id/eprint/268356
ISSN: 0967-0661
PURE UUID: 244f7f93-bf83-4333-a88b-5a7c4ac1f3cd
ORCID for Eric Rogers: ORCID iD orcid.org/0000-0003-0179-9398

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Date deposited: 06 Jan 2010 15:01
Last modified: 03 Dec 2019 02:04

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