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Kinect-based assessment of proximal arm non-use after a stroke
BACKGROUND: After a stroke, during seated reaching with their paretic upper limb, many patients spontaneously replace the use of their arm by trunk compensation movements, even though they are able to use their arm when forced to do so. We previously quantified this proximal arm non-use (PANU) with...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6236999/ https://www.ncbi.nlm.nih.gov/pubmed/30428896 http://dx.doi.org/10.1186/s12984-018-0451-2 |
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author | Bakhti, K. K. A. Laffont, I. Muthalib, M. Froger, J. Mottet, D. |
author_facet | Bakhti, K. K. A. Laffont, I. Muthalib, M. Froger, J. Mottet, D. |
author_sort | Bakhti, K. K. A. |
collection | PubMed |
description | BACKGROUND: After a stroke, during seated reaching with their paretic upper limb, many patients spontaneously replace the use of their arm by trunk compensation movements, even though they are able to use their arm when forced to do so. We previously quantified this proximal arm non-use (PANU) with a motion capture system (Zebris, CMS20s). The aim of this study was to validate a low-cost Microsoft Kinect-based system against the CMS20s reference system to diagnose PANU. METHODS: In 19 hemiparetic stroke individuals, the PANU score, reach length, trunk length, and proximal arm use (PAU) were measured during seated reaching simultaneously by the Kinect (v2) and the CMS20s over two testing sessions separated by two hours. RESULTS: Intraclass correlation coefficients (ICC) and linear regression analysis showed that the PANU score (ICC = 0.96, r(2) = 0.92), reach length (ICC = 0.81, r(2) = 0.68), trunk length (ICC = 0.97, r(2) = 0.94) and PAU (ICC = 0.97, r(2) = 0.94) measured using the Kinect were strongly related to those measured using the CMS20s. The PANU scores showed good test-retest reliability for both the Kinect (ICC = 0.76) and CMS20s (ICC = 0.72). Bland and Altman plots showed slightly reduced PANU scores in the re-test session for both systems (Kinect: − 4.25 ± 6.76; CMS20s: − 4.71 ± 7.88), which suggests a practice effect. CONCLUSION: We showed that the Kinect could accurately and reliably assess PANU, reach length, trunk length and PAU during seated reaching in post stroke individuals. We conclude that the Kinect can offer a low-cost and widely available solution to clinically assess PANU for individualised rehabilitation and to monitor the progress of paretic arm recovery. TRIAL REGISTRATION: The study was approved by The Ethics Committee of Montpellier, France (N°ID-RCB: 2014-A00395–42) and registered in Clinical Trial (N° NCT02326688, Registered on 15 December 2014, https://clinicaltrials.gov/ct2/show/results/NCT02326688). |
format | Online Article Text |
id | pubmed-6236999 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-62369992018-11-23 Kinect-based assessment of proximal arm non-use after a stroke Bakhti, K. K. A. Laffont, I. Muthalib, M. Froger, J. Mottet, D. J Neuroeng Rehabil Research BACKGROUND: After a stroke, during seated reaching with their paretic upper limb, many patients spontaneously replace the use of their arm by trunk compensation movements, even though they are able to use their arm when forced to do so. We previously quantified this proximal arm non-use (PANU) with a motion capture system (Zebris, CMS20s). The aim of this study was to validate a low-cost Microsoft Kinect-based system against the CMS20s reference system to diagnose PANU. METHODS: In 19 hemiparetic stroke individuals, the PANU score, reach length, trunk length, and proximal arm use (PAU) were measured during seated reaching simultaneously by the Kinect (v2) and the CMS20s over two testing sessions separated by two hours. RESULTS: Intraclass correlation coefficients (ICC) and linear regression analysis showed that the PANU score (ICC = 0.96, r(2) = 0.92), reach length (ICC = 0.81, r(2) = 0.68), trunk length (ICC = 0.97, r(2) = 0.94) and PAU (ICC = 0.97, r(2) = 0.94) measured using the Kinect were strongly related to those measured using the CMS20s. The PANU scores showed good test-retest reliability for both the Kinect (ICC = 0.76) and CMS20s (ICC = 0.72). Bland and Altman plots showed slightly reduced PANU scores in the re-test session for both systems (Kinect: − 4.25 ± 6.76; CMS20s: − 4.71 ± 7.88), which suggests a practice effect. CONCLUSION: We showed that the Kinect could accurately and reliably assess PANU, reach length, trunk length and PAU during seated reaching in post stroke individuals. We conclude that the Kinect can offer a low-cost and widely available solution to clinically assess PANU for individualised rehabilitation and to monitor the progress of paretic arm recovery. TRIAL REGISTRATION: The study was approved by The Ethics Committee of Montpellier, France (N°ID-RCB: 2014-A00395–42) and registered in Clinical Trial (N° NCT02326688, Registered on 15 December 2014, https://clinicaltrials.gov/ct2/show/results/NCT02326688). BioMed Central 2018-11-14 /pmc/articles/PMC6236999/ /pubmed/30428896 http://dx.doi.org/10.1186/s12984-018-0451-2 Text en © The Author(s). 2018 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 Bakhti, K. K. A. Laffont, I. Muthalib, M. Froger, J. Mottet, D. Kinect-based assessment of proximal arm non-use after a stroke |
title | Kinect-based assessment of proximal arm non-use after a stroke |
title_full | Kinect-based assessment of proximal arm non-use after a stroke |
title_fullStr | Kinect-based assessment of proximal arm non-use after a stroke |
title_full_unstemmed | Kinect-based assessment of proximal arm non-use after a stroke |
title_short | Kinect-based assessment of proximal arm non-use after a stroke |
title_sort | kinect-based assessment of proximal arm non-use after a stroke |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6236999/ https://www.ncbi.nlm.nih.gov/pubmed/30428896 http://dx.doi.org/10.1186/s12984-018-0451-2 |
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