Electrical stimulation and iterative learning control for functional recovery in the upper limb post-stroke
Electrical stimulation and iterative learning control for functional recovery in the upper limb post-stroke
Therapies using functional electrical stimulation (FES) in conjunction with practice of everyday tasks have proven effective in facilitating recovery of upper limb function following stroke. The aim of the current study is to develop a multi-channel electrical stimulation system that precisely controls the assistance provided in goal-orientated tasks through use of advanced model-based ‘iterative learning control’ (ILC) algorithms to facilitate functional motor recovery of the upper limb post-stroke. FES was applied to three muscle groups in the upper limb (the anterior deltoid, triceps and wrist extensors) to assist hemiparetic, chronic stroke participants to perform a series of functional tasks with real objects, including closing a drawer, turning on a light switch and repositioning an object. Position data from the participants’ impaired upper limb was collected using a Microsoft Kinect® and was compared to an ideal reference. ILC used data from previous attempts at the task to moderate the FES signals applied to each muscle group on a trial by trial basis to reduce performance error whilst supporting voluntary effort by the participant. The clinical trial is on-going. Preliminary results show improvements in performance accuracy for each muscle group, demonstrating the feasibility of applying precisely controlled FES to three muscle groups in the upper limb to facilitate functional reach and grasp movements post stroke.
Meadmore, Katie
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Exell, Timothy
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Hughes, Ann-Marie
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Hallewell, E.
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Freeman, Christopher
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Kutlu, Mustafa
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Burridge, Jane
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Rogers, E.
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Meadmore, Katie
4b63707b-4c44-486c-958e-e84645e7ed33
Exell, Timothy
eab3e272-643a-4a55-82a6-2949d0dc0e01
Hughes, Ann-Marie
11239f51-de47-4445-9a0d-5b82ddc11dea
Hallewell, E.
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Freeman, Christopher
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Kutlu, Mustafa
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Burridge, Jane
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Rogers, E.
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Meadmore, Katie, Exell, Timothy, Hughes, Ann-Marie, Hallewell, E., Freeman, Christopher, Kutlu, Mustafa, Burridge, Jane and Rogers, E.
(2013)
Electrical stimulation and iterative learning control for functional recovery in the upper limb post-stroke.
International Conference on Rehabilitation Robotics 2013.
24 - 26 Jun 2013.
(doi:10.1109/ICORR.2013.6650359).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Therapies using functional electrical stimulation (FES) in conjunction with practice of everyday tasks have proven effective in facilitating recovery of upper limb function following stroke. The aim of the current study is to develop a multi-channel electrical stimulation system that precisely controls the assistance provided in goal-orientated tasks through use of advanced model-based ‘iterative learning control’ (ILC) algorithms to facilitate functional motor recovery of the upper limb post-stroke. FES was applied to three muscle groups in the upper limb (the anterior deltoid, triceps and wrist extensors) to assist hemiparetic, chronic stroke participants to perform a series of functional tasks with real objects, including closing a drawer, turning on a light switch and repositioning an object. Position data from the participants’ impaired upper limb was collected using a Microsoft Kinect® and was compared to an ideal reference. ILC used data from previous attempts at the task to moderate the FES signals applied to each muscle group on a trial by trial basis to reduce performance error whilst supporting voluntary effort by the participant. The clinical trial is on-going. Preliminary results show improvements in performance accuracy for each muscle group, demonstrating the feasibility of applying precisely controlled FES to three muscle groups in the upper limb to facilitate functional reach and grasp movements post stroke.
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e-pub ahead of print date: 26 June 2013
Venue - Dates:
International Conference on Rehabilitation Robotics 2013, 2013-06-24 - 2013-06-26
Organisations:
Physical & Rehabilitation Health, EEE, Southampton Wireless Group
Identifiers
Local EPrints ID: 350936
URI: http://eprints.soton.ac.uk/id/eprint/350936
PURE UUID: 10db10e8-0d45-4807-8f7a-659d78b87469
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Date deposited: 10 Apr 2013 16:07
Last modified: 11 Dec 2024 02:39
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Contributors
Author:
Timothy Exell
Author:
E. Hallewell
Author:
Christopher Freeman
Author:
Mustafa Kutlu
Author:
E. Rogers
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