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Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study
BACKGROUND: Intensive robot-assisted training of the upper limb after stroke can reduce motor impairment, even at the chronic stage. However, the effectiveness of practice for recovery depends on the selection of the practised movements. We hypothesized that rehabilitation can be optimized by select...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425657/ https://www.ncbi.nlm.nih.gov/pubmed/30894192 http://dx.doi.org/10.1186/s12984-019-0513-0 |
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author | Rosenthal, Orna Wing, Alan M. Wyatt, Jeremy L. Punt, David Brownless, Briony Ko-Ko, Chit Miall, R. Christopher |
author_facet | Rosenthal, Orna Wing, Alan M. Wyatt, Jeremy L. Punt, David Brownless, Briony Ko-Ko, Chit Miall, R. Christopher |
author_sort | Rosenthal, Orna |
collection | PubMed |
description | BACKGROUND: Intensive robot-assisted training of the upper limb after stroke can reduce motor impairment, even at the chronic stage. However, the effectiveness of practice for recovery depends on the selection of the practised movements. We hypothesized that rehabilitation can be optimized by selecting the movements to be practiced based on the trainee’s performance profile. METHODS: We present a novel principle (‘steepest gradients’) for performance-based selection of movements. The principle is based on mapping motor performance across a workspace and then selecting movements located at regions of the steepest transition between better and worse performance. To assess the benefit of this principle we compared the effect of 15 sessions of robot-assisted reaching training on upper-limb motor impairment, between two groups of people who have moderate-to-severe chronic upper-limb hemiparesis due to stroke. The test group (N = 7) received steepest gradients-based training, iteratively selected according to the steepest gradients principle with weekly remapping, whereas the control group (N = 9) received a standard “centre-out” reaching training. Training intensity was identical. RESULTS: Both groups showed improvement in Fugl-Meyer upper-extremity scores (the primary outcome measure). Moreover, the test group showed significantly greater improvement (twofold) compared to control. The score remained elevated, on average, for at least 4 weeks although the additional benefit of the steepest-gradients -based training diminished relative to control. CONCLUSIONS: This study provides a proof of concept for the superior benefit of performance-based selection of practiced movements in reducing upper-limb motor impairment due to stroke. This added benefit was most evident in the short term, suggesting that performance-based steepest-gradients training may be effective in increasing the rate of initial phase of practice-based recovery; we discuss how long-term retention may also be improved. TRIAL REGISTRATION: ISRCTN, ISRCTN65226825, registered 12 June 2018 - Retrospectively registered, ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-019-0513-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6425657 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64256572019-04-01 Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study Rosenthal, Orna Wing, Alan M. Wyatt, Jeremy L. Punt, David Brownless, Briony Ko-Ko, Chit Miall, R. Christopher J Neuroeng Rehabil Research BACKGROUND: Intensive robot-assisted training of the upper limb after stroke can reduce motor impairment, even at the chronic stage. However, the effectiveness of practice for recovery depends on the selection of the practised movements. We hypothesized that rehabilitation can be optimized by selecting the movements to be practiced based on the trainee’s performance profile. METHODS: We present a novel principle (‘steepest gradients’) for performance-based selection of movements. The principle is based on mapping motor performance across a workspace and then selecting movements located at regions of the steepest transition between better and worse performance. To assess the benefit of this principle we compared the effect of 15 sessions of robot-assisted reaching training on upper-limb motor impairment, between two groups of people who have moderate-to-severe chronic upper-limb hemiparesis due to stroke. The test group (N = 7) received steepest gradients-based training, iteratively selected according to the steepest gradients principle with weekly remapping, whereas the control group (N = 9) received a standard “centre-out” reaching training. Training intensity was identical. RESULTS: Both groups showed improvement in Fugl-Meyer upper-extremity scores (the primary outcome measure). Moreover, the test group showed significantly greater improvement (twofold) compared to control. The score remained elevated, on average, for at least 4 weeks although the additional benefit of the steepest-gradients -based training diminished relative to control. CONCLUSIONS: This study provides a proof of concept for the superior benefit of performance-based selection of practiced movements in reducing upper-limb motor impairment due to stroke. This added benefit was most evident in the short term, suggesting that performance-based steepest-gradients training may be effective in increasing the rate of initial phase of practice-based recovery; we discuss how long-term retention may also be improved. TRIAL REGISTRATION: ISRCTN, ISRCTN65226825, registered 12 June 2018 - Retrospectively registered, ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-019-0513-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-03-20 /pmc/articles/PMC6425657/ /pubmed/30894192 http://dx.doi.org/10.1186/s12984-019-0513-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Rosenthal, Orna Wing, Alan M. Wyatt, Jeremy L. Punt, David Brownless, Briony Ko-Ko, Chit Miall, R. Christopher Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study |
title | Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study |
title_full | Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study |
title_fullStr | Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study |
title_full_unstemmed | Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study |
title_short | Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study |
title_sort | boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements – a pilot study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425657/ https://www.ncbi.nlm.nih.gov/pubmed/30894192 http://dx.doi.org/10.1186/s12984-019-0513-0 |
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