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A postural unloading task to assess fast corrective responses in the upper limb following stroke
BACKGROUND: Robotic technologies to measure human behavior are emerging as a new approach to assess brain function. Recently, we developed a robot-based postural Load Task to assess corrective responses to mechanical disturbances to the arm and found impairments in many participants with stroke comp...
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/PMC6350318/ https://www.ncbi.nlm.nih.gov/pubmed/30691482 http://dx.doi.org/10.1186/s12984-019-0483-2 |
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author | Lowrey, Catherine R. Bourke, Teige C. Bagg, Stephen D. Dukelow, Sean P. Scott, Stephen H. |
author_facet | Lowrey, Catherine R. Bourke, Teige C. Bagg, Stephen D. Dukelow, Sean P. Scott, Stephen H. |
author_sort | Lowrey, Catherine R. |
collection | PubMed |
description | BACKGROUND: Robotic technologies to measure human behavior are emerging as a new approach to assess brain function. Recently, we developed a robot-based postural Load Task to assess corrective responses to mechanical disturbances to the arm and found impairments in many participants with stroke compared to a healthy cohort (Bourke et al, J NeuroEngineering Rehabil 12: 7, 2015). However, a striking feature was the large range and skewed distribution of healthy performance. This likely reflects the use of different strategies across the healthy control sample, making it difficult to identify impairments. Here, we developed an intuitive “Unload Task”. We hypothesized this task would reduce healthy performance variability and improve the detection of impairment following stroke. METHODS: Performance on the Load and Unload Task in the KINARM exoskeleton robot was directly compared for healthy control (n = 107) and stroke (n = 31) participants. The goal was to keep a cursor representing the hand inside a virtual target and return “quickly and accurately” if the robot applied (or removed) an unexpected load to the arm (0.5–1.5 Nm). Several kinematic parameters quantified performance. Impairment was defined as performance outside the 95% of controls (corrected for age, sex and handedness). Task Scores were calculated using standardized parameter scores reflecting overall task performance. RESULTS: The distribution of healthy control performance was smaller and less skewed for the Unload Task compared to the Load Task. Fewer task outliers (outside 99.9 percentile for controls) were removed from the Unload Task (3.7%) compared to the Load Task (7.4%) when developing normative models of performance. Critically, more participants with stroke failed the Unload Task based on Task Score with their affected arm (68%) compared to the Load Task (23%). More impairments were found at the parameter level for the Unload (median = 52%) compared to Load Task (median = 29%). CONCLUSIONS: The Unload Task provides an improved approach to assess fast corrective responses of the arm. We found that corrective responses are impaired in persons living with stroke, often equally in both arms. Impairments in generating rapid motor corrections may place individuals at greater risk of falls when they move and interact in the environment. |
format | Online Article Text |
id | pubmed-6350318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63503182019-02-04 A postural unloading task to assess fast corrective responses in the upper limb following stroke Lowrey, Catherine R. Bourke, Teige C. Bagg, Stephen D. Dukelow, Sean P. Scott, Stephen H. J Neuroeng Rehabil Research BACKGROUND: Robotic technologies to measure human behavior are emerging as a new approach to assess brain function. Recently, we developed a robot-based postural Load Task to assess corrective responses to mechanical disturbances to the arm and found impairments in many participants with stroke compared to a healthy cohort (Bourke et al, J NeuroEngineering Rehabil 12: 7, 2015). However, a striking feature was the large range and skewed distribution of healthy performance. This likely reflects the use of different strategies across the healthy control sample, making it difficult to identify impairments. Here, we developed an intuitive “Unload Task”. We hypothesized this task would reduce healthy performance variability and improve the detection of impairment following stroke. METHODS: Performance on the Load and Unload Task in the KINARM exoskeleton robot was directly compared for healthy control (n = 107) and stroke (n = 31) participants. The goal was to keep a cursor representing the hand inside a virtual target and return “quickly and accurately” if the robot applied (or removed) an unexpected load to the arm (0.5–1.5 Nm). Several kinematic parameters quantified performance. Impairment was defined as performance outside the 95% of controls (corrected for age, sex and handedness). Task Scores were calculated using standardized parameter scores reflecting overall task performance. RESULTS: The distribution of healthy control performance was smaller and less skewed for the Unload Task compared to the Load Task. Fewer task outliers (outside 99.9 percentile for controls) were removed from the Unload Task (3.7%) compared to the Load Task (7.4%) when developing normative models of performance. Critically, more participants with stroke failed the Unload Task based on Task Score with their affected arm (68%) compared to the Load Task (23%). More impairments were found at the parameter level for the Unload (median = 52%) compared to Load Task (median = 29%). CONCLUSIONS: The Unload Task provides an improved approach to assess fast corrective responses of the arm. We found that corrective responses are impaired in persons living with stroke, often equally in both arms. Impairments in generating rapid motor corrections may place individuals at greater risk of falls when they move and interact in the environment. BioMed Central 2019-01-28 /pmc/articles/PMC6350318/ /pubmed/30691482 http://dx.doi.org/10.1186/s12984-019-0483-2 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 Lowrey, Catherine R. Bourke, Teige C. Bagg, Stephen D. Dukelow, Sean P. Scott, Stephen H. A postural unloading task to assess fast corrective responses in the upper limb following stroke |
title | A postural unloading task to assess fast corrective responses in the upper limb following stroke |
title_full | A postural unloading task to assess fast corrective responses in the upper limb following stroke |
title_fullStr | A postural unloading task to assess fast corrective responses in the upper limb following stroke |
title_full_unstemmed | A postural unloading task to assess fast corrective responses in the upper limb following stroke |
title_short | A postural unloading task to assess fast corrective responses in the upper limb following stroke |
title_sort | postural unloading task to assess fast corrective responses in the upper limb following stroke |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350318/ https://www.ncbi.nlm.nih.gov/pubmed/30691482 http://dx.doi.org/10.1186/s12984-019-0483-2 |
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