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Iterative learning control for robotic-assisted upper limb stroke rehabilitation in the presence of muscle fatigue

Iterative learning control for robotic-assisted upper limb stroke rehabilitation in the presence of muscle fatigue
Iterative learning control for robotic-assisted upper limb stroke rehabilitation in the presence of muscle fatigue
The use of iterative learning control to regulate assistive functional electrical stimulation applied to the muscles of patients undergoing robotic-assisted upper limb stroke rehabilitation has been followed through to small scale clinical trials. These trials confirmed that an increase in patient ability to complete the specified task also led to a reduction in the level of electrical stimulation required. This previous work assumed that the effects of muscle fatigue could be neglected but if a patient suffers fatigue during a rehabilitation session then their the session goals are not achieved or, more likely, the session must be abandoned due to the time limits imposed by the ethical approval required to conduct such sessions. In this paper the results of the first investigation into enhancing the control scheme to remove or lessen the effects of fatigue and hence make better use of the time available for a session are given. The scheme considered adds a feedback loop around the muscle model used, where the performance results given are based on a model for the dynamics constructed using patient data collected in previous clinical trials.
0967-0661
63-72
Xu, W.
a5f7f937-d80c-471b-81d2-7a330b8241cc
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Xu, W.
a5f7f937-d80c-471b-81d2-7a330b8241cc
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72

Xu, W., Chu, Bing and Rogers, E. (2014) Iterative learning control for robotic-assisted upper limb stroke rehabilitation in the presence of muscle fatigue. Control Engineering Practice, 31, 63-72. (doi:10.1016/j.conengprac.2014.05.009).

Record type: Article

Abstract

The use of iterative learning control to regulate assistive functional electrical stimulation applied to the muscles of patients undergoing robotic-assisted upper limb stroke rehabilitation has been followed through to small scale clinical trials. These trials confirmed that an increase in patient ability to complete the specified task also led to a reduction in the level of electrical stimulation required. This previous work assumed that the effects of muscle fatigue could be neglected but if a patient suffers fatigue during a rehabilitation session then their the session goals are not achieved or, more likely, the session must be abandoned due to the time limits imposed by the ethical approval required to conduct such sessions. In this paper the results of the first investigation into enhancing the control scheme to remove or lessen the effects of fatigue and hence make better use of the time available for a session are given. The scheme considered adds a feedback loop around the muscle model used, where the performance results given are based on a model for the dynamics constructed using patient data collected in previous clinical trials.

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e-pub ahead of print date: 5 August 2014
Published date: October 2014
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 363007
URI: http://eprints.soton.ac.uk/id/eprint/363007
ISSN: 0967-0661
PURE UUID: ebfb3ef4-78c4-4a22-af74-d094f603664e
ORCID for Bing Chu: ORCID iD orcid.org/0000-0002-2711-8717
ORCID for E. Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 10 Mar 2014 18:50
Last modified: 03 Dec 2019 02:04

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