Douglass-Kirk, Pedro;
Grierson, Mick;
Ward, Nick S;
Brander, Fran;
Kelly, Kate;
Chegwidden, Will;
Shivji, Dhiren;
(2022)
Real-time auditory feedback may reduce abnormal movements in patients with chronic stroke.
Disability and Rehabilitation
pp. 1-7.
10.1080/09638288.2022.2037751.
(In press).
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Abstract
PURPOSE: The current pilot study assesses the use of real-time auditory feedback to help reduce abnormal movements during an active reaching task in patients with chronic stroke. MATERIALS AND METHODS: 20 patients with chronic stroke completed the study with full datasets (age: M = 53 SD = 14; sex: male = 75%; time since stroke in months: M = 34, SD = 33). Patients undertook 100 repetitions of an active reaching task while listening to self-selected music which automatically muted when abnormal movement was detected, determined by thresholds set by clinical therapists. A within-subject design with two conditions (with auditory feedback vs. without auditory feedback) presented in a randomised counterbalanced order was used. The dependent variable was the duration of abnormal movement as a proportion of trial duration. RESULTS: A significant reduction in the duration of abnormal movement was observed when patients received auditory feedback, F(1,18) = 9.424, p = 0.007, with a large effect size (partial η2 = 0.344). CONCLUSIONS: Patients with chronic stroke can make use of real-time auditory feedback to increase the proportion of time they spend in optimal movement patterns. The approach provides a motivating framework that encourages high dose with a key focus on quality of movement. Trial Registration: ISRCTN12969079 https://www.isrctn.com/ISRCTN12969079 ISRTCN trial registration REF: ISRCTN12969079IMPLICATIONS FOR REHABILITATIONMovement quality during upper limb rehabilitation should be targeted as part of a well-balanced rehabilitation programme.Auditory feedback is a useful tool to help patients with chronic stroke reduce compensatory movements.
| Type: | Article |
|---|---|
| Title: | Real-time auditory feedback may reduce abnormal movements in patients with chronic stroke |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/09638288.2022.2037751 |
| Publisher version: | https://doi.org/10.1080/09638288.2022.2037751 |
| Language: | English |
| Additional information: | © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Rehabilitation, compensation, kinematics, machine learning, movement |
| UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10144900 |
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