Muscle co-contraction patterns in robot-mediated force field learning to guide specific muscle group training

Article


Pizzamiglio, Sara, Desowska, Adela, Shojaii, Pegah, Taga, Myriam and Turner, D. 2017. Muscle co-contraction patterns in robot-mediated force field learning to guide specific muscle group training. NeuroRehabilitation. 41 (1), pp. 17-29.
AuthorsPizzamiglio, Sara, Desowska, Adela, Shojaii, Pegah, Taga, Myriam and Turner, D.
Abstract

BACKGROUND: Muscle co-contraction is a strategy of increasing movement accuracy and stability employed in dealing with perturbation of movement. It is often seen in neuropathological populations. The direction of movement influences the pattern of co-contraction, but not all movements are easily achievable for populations with motor deficits. Manipulating the direction of the force instead, may be a promising rehabilitation protocol to train movement with use of a co-contraction reduction strategy. Force field learning paradigms provide a well described procedure to evoke and test muscle co-contraction.

OBJECTIVE: The aim of this study was to test the muscle co-contraction pattern in a wide range of arm muscles in different force-field directions utilising a robot-assisted force field learning paradigm of motor adaptation.

METHOD: 42 participants volunteered to participate in a study utilising robot-assisted motor adaptation paradigm with clockwise or counter-clockwise force field. Kinematics and surface electromyography (EMG) of eight arm muscles has been measured.

RESULTS: Both muscle activation and co-contraction was earlier and stronger in flexors in clockwise condition and in extensors in the counter-clockwise condition.

CONCLUSIONS: Manipulating the force field direction leads to changes in the pattern of muscle co-contraction.

KeywordsMotor adaptation; force-field learning; EMG; co-contraction; rehabilitation
JournalNeuroRehabilitation
Journal citation41 (1), pp. 17-29
ISSN1053-8135
1878-6448
Year2017
PublisherIOS Press
Accepted author manuscript
Digital Object Identifier (DOI)doi:10.3233/NRE-171453
Publication dates
Print22 Jul 2017
Publication process dates
Deposited09 May 2017
Accepted30 Jan 2017
Copyright information© 2017 The authors. The final publication is available at IOS Press through http://dx.doi.org/10.3233/NRE-171453
LicenseAll rights reserved
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