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Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton
BACKGROUND: The clinical evaluation of the upper limb of severely impaired stroke patient is challenging. Sensor-based assessments may allow for an objective evaluation of this patient population. This study investigated the validity of a device-assisted approach in comparison to the clinical outcom...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170809/ https://www.ncbi.nlm.nih.gov/pubmed/34078400 http://dx.doi.org/10.1186/s12984-021-00875-7 |
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author | Grimm, Florian Kraugmann, Jelena Naros, Georgios Gharabaghi, Alireza |
author_facet | Grimm, Florian Kraugmann, Jelena Naros, Georgios Gharabaghi, Alireza |
author_sort | Grimm, Florian |
collection | PubMed |
description | BACKGROUND: The clinical evaluation of the upper limb of severely impaired stroke patient is challenging. Sensor-based assessments may allow for an objective evaluation of this patient population. This study investigated the validity of a device-assisted approach in comparison to the clinical outcome that it is supposed to reflect. METHODS: In nineteen severely impaired chronic stroke patients, we applied a gravity-compensating, multi-joint arm exoskeleton (Armeo Spring) and compared this sensor-based assessment with the clinical outcome measure Upper Extremity Fugl-Meyer Assessment (UE-FMA) scale. Specifically, we assessed separately and subsequently the range of motion in joint space for four single joints (i.e., wrist, elbow and shoulder flexion/extension (FE), and shoulder internal/external rotation (IER)), and the closing and opening of the hand with a pressure sensor placed in the handle. RESULTS: Within the kinematic parameters, a strong correlation was observed between wrist and elbow FE (r > 0.7, p < 0.003; Bonferroni corrected). The UE-FMA was significantly predicted by a multiple regression model (F (5, 13) = 12.22, p < 0.0005, adj. R(2) = 0.83). Both shoulder IER and grip pressure added significantly (p < 0.05) to the prediction with the standardized coefficients β of 0.55 and 0.38, respectively. CONCLUSIONS: By applying an exoskeleton-based self-contained evaluation of single-joint movements, a clinically valid assessment of the upper limb range of motion in severely impaired stroke patients is feasible. Shoulder IER contributed most relevantly to the prediction of the clinical status. These findings need to be confirmed in a large, independent patient cohort. |
format | Online Article Text |
id | pubmed-8170809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81708092021-06-02 Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton Grimm, Florian Kraugmann, Jelena Naros, Georgios Gharabaghi, Alireza J Neuroeng Rehabil Research BACKGROUND: The clinical evaluation of the upper limb of severely impaired stroke patient is challenging. Sensor-based assessments may allow for an objective evaluation of this patient population. This study investigated the validity of a device-assisted approach in comparison to the clinical outcome that it is supposed to reflect. METHODS: In nineteen severely impaired chronic stroke patients, we applied a gravity-compensating, multi-joint arm exoskeleton (Armeo Spring) and compared this sensor-based assessment with the clinical outcome measure Upper Extremity Fugl-Meyer Assessment (UE-FMA) scale. Specifically, we assessed separately and subsequently the range of motion in joint space for four single joints (i.e., wrist, elbow and shoulder flexion/extension (FE), and shoulder internal/external rotation (IER)), and the closing and opening of the hand with a pressure sensor placed in the handle. RESULTS: Within the kinematic parameters, a strong correlation was observed between wrist and elbow FE (r > 0.7, p < 0.003; Bonferroni corrected). The UE-FMA was significantly predicted by a multiple regression model (F (5, 13) = 12.22, p < 0.0005, adj. R(2) = 0.83). Both shoulder IER and grip pressure added significantly (p < 0.05) to the prediction with the standardized coefficients β of 0.55 and 0.38, respectively. CONCLUSIONS: By applying an exoskeleton-based self-contained evaluation of single-joint movements, a clinically valid assessment of the upper limb range of motion in severely impaired stroke patients is feasible. Shoulder IER contributed most relevantly to the prediction of the clinical status. These findings need to be confirmed in a large, independent patient cohort. BioMed Central 2021-06-02 /pmc/articles/PMC8170809/ /pubmed/34078400 http://dx.doi.org/10.1186/s12984-021-00875-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Grimm, Florian Kraugmann, Jelena Naros, Georgios Gharabaghi, Alireza Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title | Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_full | Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_fullStr | Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_full_unstemmed | Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_short | Clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
title_sort | clinical validation of kinematic assessments of post-stroke upper limb movements with a multi-joint arm exoskeleton |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170809/ https://www.ncbi.nlm.nih.gov/pubmed/34078400 http://dx.doi.org/10.1186/s12984-021-00875-7 |
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