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Goal Orientated stroke rehabilitation utilising electrical stimulation, iterative learning and Microsoft Kinect

Goal Orientated stroke rehabilitation utilising electrical stimulation, iterative learning and Microsoft Kinect
Goal Orientated stroke rehabilitation utilising electrical stimulation, iterative learning and Microsoft Kinect
An upper-limb stroke rehabilitation system is developed that assists patients in performing real world functionally relevant reaching tasks. The system provides de-weighting of the arm via a simple spring support whilst functional electrical stimulation is applied to the anterior deltoid and triceps via surface electrodes, and to the wrist and hand extensors via a 40 element surface electrode array. Iterative learning control (ILC) is used to mediate the electrical stimulation, and updates the stimulation signal applied to each muscle group based on the error between the ideal and actual movement in the previous attempt. The control system applies the minimum amount of stimulation required, maximising voluntary effort. Low-cost, markerless motion tracking is provided via a Microsoft Kinect, with hand and wrist data provided by an electrogoniometer or data glove. The system is described and initial experimental results are presented for a stroke patient starting treatment.
Exell, Timothy
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Freeman, Christopher
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Meadmore, Katie
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Kutlu, Mustafa
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Hallewell, Emma
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Hughes, Ann-Marie
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Burridge, Jane H.
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Rogers, Eric
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Exell, Timothy
eab3e272-643a-4a55-82a6-2949d0dc0e01
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Meadmore, Katie
4b63707b-4c44-486c-958e-e84645e7ed33
Kutlu, Mustafa
4e99ab81-ef5e-4c66-b042-8aeee432f468
Hallewell, Emma
8f672810-88f1-4358-b0cf-ac8920c79474
Hughes, Ann-Marie
11239f51-de47-4445-9a0d-5b82ddc11dea
Burridge, Jane H.
0110e9ea-0884-4982-a003-cb6307f38f64
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72

Exell, Timothy, Freeman, Christopher, Meadmore, Katie, Kutlu, Mustafa, Hallewell, Emma, Hughes, Ann-Marie, Burridge, Jane H. and Rogers, Eric (2013) Goal Orientated stroke rehabilitation utilising electrical stimulation, iterative learning and Microsoft Kinect. International Conference on Rehabilitation Robotics 2013. 24 - 26 Jun 2013.

Record type: Conference or Workshop Item (Paper)

Abstract

An upper-limb stroke rehabilitation system is developed that assists patients in performing real world functionally relevant reaching tasks. The system provides de-weighting of the arm via a simple spring support whilst functional electrical stimulation is applied to the anterior deltoid and triceps via surface electrodes, and to the wrist and hand extensors via a 40 element surface electrode array. Iterative learning control (ILC) is used to mediate the electrical stimulation, and updates the stimulation signal applied to each muscle group based on the error between the ideal and actual movement in the previous attempt. The control system applies the minimum amount of stimulation required, maximising voluntary effort. Low-cost, markerless motion tracking is provided via a Microsoft Kinect, with hand and wrist data provided by an electrogoniometer or data glove. The system is described and initial experimental results are presented for a stroke patient starting treatment.

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More information

Published date: February 2013
Venue - Dates: International Conference on Rehabilitation Robotics 2013, 2013-06-24 - 2013-06-26
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 350060
URI: http://eprints.soton.ac.uk/id/eprint/350060
PURE UUID: 4098ceb1-fc61-4383-89ef-b74208363b01
ORCID for Katie Meadmore: ORCID iD orcid.org/0000-0001-5378-8370
ORCID for Ann-Marie Hughes: ORCID iD orcid.org/0000-0002-3958-8206
ORCID for Jane H. Burridge: ORCID iD orcid.org/0000-0003-3497-6725
ORCID for Eric Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 19 Mar 2013 11:16
Last modified: 15 Mar 2024 03:25

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Contributors

Author: Timothy Exell
Author: Christopher Freeman
Author: Katie Meadmore ORCID iD
Author: Mustafa Kutlu
Author: Emma Hallewell
Author: Eric Rogers ORCID iD

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