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Computational models of upper limb movement during functional reaching tasks for application in electrical stimulation based stroke rehabilitation

Computational models of upper limb movement during functional reaching tasks for application in electrical stimulation based stroke rehabilitation
Computational models of upper limb movement during functional reaching tasks for application in electrical stimulation based stroke rehabilitation
Introduction: Functional electrical stimulation (FES) has been shown to be an effective approach to upperlimb
stroke rehabilitation, where it assists patients' arm and shoulder movement. Model-based FES controllers
have recently confirmed significant potential to improve accuracy of functional reaching tasks, but
they typically require a reference trajectory to track. No upper limb FES control scheme has yet embedded
a computational model of the task, however this is critical to ensure the controller reinforces the intended
movement with high accuracy. This paper derives a computational motor control model of the task which
can be embedded in FES control schemes, removing the need for a predefined reference trajectory.
Methods: Kinematic data were collected using a Vicon motion capture system from unimpaired (N = 14)
participants while they performed two functional reaching tasks in which they: 1) pushed a light switch, and
2) closed a drawer. In each case they starting and finished the movement with their hand on their knee.
Dynamic models of each patient's arm were derived using estimated mass, inertial and stiffness parameters.
Each task was posed as an optimization problem with position and velocity boundary constraints, and these
were solved using iterative algorithms to yield computational models of movement.
Results: For the case of unimpaired participants, the experimentally recorded joint angles were compared
with those derived in simulation using the model, and were found to fit closely (mean fitting > 85%).
Conclusion: Functional movements have been accurately modelled as constrained optimization problems
involving dynamic models of unimpaired participants' arms. This extends previous computational models of
human movement, and shows that they can be solved using iterative methods. Moreover, these methods
are suitable to be employed experimentally in future stroke rehabilitation trials using FES to assist task completion
in a manner corresponding to unimpaired movement. This hence ensures that assistance is aligned
with voluntary intention, and in-so-doing maximizes the potential effectiveness of treatment.
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Exell, Timothy
eab3e272-643a-4a55-82a6-2949d0dc0e01
Meadmore, Katie
4b63707b-4c44-486c-958e-e84645e7ed33
Hallewell, E.
6c2fdbaf-e8f8-4693-9150-889d9b021b92
Hughes, Ann-Marie
11239f51-de47-4445-9a0d-5b82ddc11dea
Burridge, J.H.
0110e9ea-0884-4982-a003-cb6307f38f64
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Exell, Timothy
eab3e272-643a-4a55-82a6-2949d0dc0e01
Meadmore, Katie
4b63707b-4c44-486c-958e-e84645e7ed33
Hallewell, E.
6c2fdbaf-e8f8-4693-9150-889d9b021b92
Hughes, Ann-Marie
11239f51-de47-4445-9a0d-5b82ddc11dea
Burridge, J.H.
0110e9ea-0884-4982-a003-cb6307f38f64

Freeman, Christopher, Exell, Timothy, Meadmore, Katie, Hallewell, E., Hughes, Ann-Marie and Burridge, J.H. (2013) Computational models of upper limb movement during functional reaching tasks for application in electrical stimulation based stroke rehabilitation. 4th European Conference on Technically Assisted Rehabilitation, Berlin, Germany.

Record type: Conference or Workshop Item (Paper)

Abstract

Introduction: Functional electrical stimulation (FES) has been shown to be an effective approach to upperlimb
stroke rehabilitation, where it assists patients' arm and shoulder movement. Model-based FES controllers
have recently confirmed significant potential to improve accuracy of functional reaching tasks, but
they typically require a reference trajectory to track. No upper limb FES control scheme has yet embedded
a computational model of the task, however this is critical to ensure the controller reinforces the intended
movement with high accuracy. This paper derives a computational motor control model of the task which
can be embedded in FES control schemes, removing the need for a predefined reference trajectory.
Methods: Kinematic data were collected using a Vicon motion capture system from unimpaired (N = 14)
participants while they performed two functional reaching tasks in which they: 1) pushed a light switch, and
2) closed a drawer. In each case they starting and finished the movement with their hand on their knee.
Dynamic models of each patient's arm were derived using estimated mass, inertial and stiffness parameters.
Each task was posed as an optimization problem with position and velocity boundary constraints, and these
were solved using iterative algorithms to yield computational models of movement.
Results: For the case of unimpaired participants, the experimentally recorded joint angles were compared
with those derived in simulation using the model, and were found to fit closely (mean fitting > 85%).
Conclusion: Functional movements have been accurately modelled as constrained optimization problems
involving dynamic models of unimpaired participants' arms. This extends previous computational models of
human movement, and shows that they can be solved using iterative methods. Moreover, these methods
are suitable to be employed experimentally in future stroke rehabilitation trials using FES to assist task completion
in a manner corresponding to unimpaired movement. This hence ensures that assistance is aligned
with voluntary intention, and in-so-doing maximizes the potential effectiveness of treatment.

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Published date: 14 March 2013
Venue - Dates: 4th European Conference on Technically Assisted Rehabilitation, Berlin, Germany, 2013-03-14
Organisations: Physical & Rehabilitation Health, EEE

Identifiers

Local EPrints ID: 348409
URI: http://eprints.soton.ac.uk/id/eprint/348409
PURE UUID: 39967b55-09f6-4094-b581-91e9a9df82d0
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 J.H. Burridge: ORCID iD orcid.org/0000-0003-3497-6725

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Date deposited: 12 Feb 2013 18:34
Last modified: 07 Oct 2020 05:03

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