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Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training
BACKGROUND: Chronic upper limb motor impairment is a common outcome of stroke. Therapeutic training can reduce motor impairment. Recently, a growing interest in evaluating motor training provided by robotic assistive devices has emerged. Robot-assisted therapy is attractive because it provides a mea...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5718133/ https://www.ncbi.nlm.nih.gov/pubmed/29208020 http://dx.doi.org/10.1186/s12984-017-0335-x |
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author | Rosenthal, Orna Wing, Alan M. Wyatt, Jeremy L. Punt, David Miall, R. Chris |
author_facet | Rosenthal, Orna Wing, Alan M. Wyatt, Jeremy L. Punt, David Miall, R. Chris |
author_sort | Rosenthal, Orna |
collection | PubMed |
description | BACKGROUND: Chronic upper limb motor impairment is a common outcome of stroke. Therapeutic training can reduce motor impairment. Recently, a growing interest in evaluating motor training provided by robotic assistive devices has emerged. Robot-assisted therapy is attractive because it provides a means of increasing practice intensity without increasing the workload of physical therapists. However, movements practised through robotic assistive devices are commonly pre-defined and fixed across individuals. More optimal training may result from individualizing the selection of the trained movements based on the individual’s impairment profile. This requires quantitative assessment of the degree of the motor impairment prior to training, in relevant movement tasks. However, standard clinical measures for profiling motor impairment after stroke are often subjective and lack precision. We have developed a novel robot-mediated method for systematic and fine-grained mapping (or profiling) of individual performance across a wide range of planar arm reaching movements. Here we describe and demonstrate this mapping method and its utilization for individualized training. We also present a novel principle for the individualized selection of training movements based on the performance maps. METHODS AND RESULTS: To demonstrate the utility of our method we present examples of 2D performance maps produced from the kinetic and kinematics data of two individuals with stroke-related upper limb hemiparesis. The maps outline distinct regions of high motor impairment. The procedure of map-based selection of training movements and the change in motor performance following training is demonstrated for one participant. CONCLUSIONS: The performance mapping method is feasible to produce (online or offline). The 2D maps are easy to interpret and to be utilized for selecting individual performance-based training. Different performance maps can be easily compared within and between individuals, which potentially has diagnostic utility. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-017-0335-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5718133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57181332017-12-08 Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training Rosenthal, Orna Wing, Alan M. Wyatt, Jeremy L. Punt, David Miall, R. Chris J Neuroeng Rehabil Methodology BACKGROUND: Chronic upper limb motor impairment is a common outcome of stroke. Therapeutic training can reduce motor impairment. Recently, a growing interest in evaluating motor training provided by robotic assistive devices has emerged. Robot-assisted therapy is attractive because it provides a means of increasing practice intensity without increasing the workload of physical therapists. However, movements practised through robotic assistive devices are commonly pre-defined and fixed across individuals. More optimal training may result from individualizing the selection of the trained movements based on the individual’s impairment profile. This requires quantitative assessment of the degree of the motor impairment prior to training, in relevant movement tasks. However, standard clinical measures for profiling motor impairment after stroke are often subjective and lack precision. We have developed a novel robot-mediated method for systematic and fine-grained mapping (or profiling) of individual performance across a wide range of planar arm reaching movements. Here we describe and demonstrate this mapping method and its utilization for individualized training. We also present a novel principle for the individualized selection of training movements based on the performance maps. METHODS AND RESULTS: To demonstrate the utility of our method we present examples of 2D performance maps produced from the kinetic and kinematics data of two individuals with stroke-related upper limb hemiparesis. The maps outline distinct regions of high motor impairment. The procedure of map-based selection of training movements and the change in motor performance following training is demonstrated for one participant. CONCLUSIONS: The performance mapping method is feasible to produce (online or offline). The 2D maps are easy to interpret and to be utilized for selecting individual performance-based training. Different performance maps can be easily compared within and between individuals, which potentially has diagnostic utility. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-017-0335-x) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-06 /pmc/articles/PMC5718133/ /pubmed/29208020 http://dx.doi.org/10.1186/s12984-017-0335-x Text en © The Author(s). 2017 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 | Methodology Rosenthal, Orna Wing, Alan M. Wyatt, Jeremy L. Punt, David Miall, R. Chris Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training |
title | Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training |
title_full | Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training |
title_fullStr | Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training |
title_full_unstemmed | Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training |
title_short | Mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training |
title_sort | mapping upper-limb motor performance after stroke - a novel method with utility for individualized motor training |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5718133/ https://www.ncbi.nlm.nih.gov/pubmed/29208020 http://dx.doi.org/10.1186/s12984-017-0335-x |
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