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Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach
Most post-stroke patients experience varying degrees of impairment in upper limb function and fine motor skills. Occupational therapy (OT) with other rehabilitation trainings is beneficial in improving the strength and dexterity of the impaired upper limb. An accurate upper limb assessment should be...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8718516/ https://www.ncbi.nlm.nih.gov/pubmed/34977858 http://dx.doi.org/10.3389/fdgth.2021.784120 |
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author | Mahmoud, Seedahmed S. Cao, Zheng Fu, Jianming Gu, Xudong Fang, Qiang |
author_facet | Mahmoud, Seedahmed S. Cao, Zheng Fu, Jianming Gu, Xudong Fang, Qiang |
author_sort | Mahmoud, Seedahmed S. |
collection | PubMed |
description | Most post-stroke patients experience varying degrees of impairment in upper limb function and fine motor skills. Occupational therapy (OT) with other rehabilitation trainings is beneficial in improving the strength and dexterity of the impaired upper limb. An accurate upper limb assessment should be conducted before prescribing upper limb OT programs. In this paper, we present a novel multisensor method for the assessment of upper limb movements that uses kinematics and physiological sensors to capture the movement of the limbs and the surface electromyogram (sEMG). These sensors are Kinect, inertial measurement unit (IMU), Xsens, and sEMG. The key assessment features of the proposed model are as follows: (1) classification of OT exercises into four classes, (2) evaluation of the quality and completion of the OT exercises, and (3) evaluation of the relationship between upper limb mobility and muscle strength in patients. According to experimental results, the overall accuracy for OT-based motion classification is 82.2%. In addition, the fusing of Kinect and Xsens data reveals that muscle strength is highly correlated with the data with a correlation coefficient (CC) of 0.88. As a result of this research, occupational therapy specialists will be able to provide early support discharge, which could alleviate the problem of the great stress that the healthcare system is experiencing today. |
format | Online Article Text |
id | pubmed-8718516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87185162022-01-01 Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach Mahmoud, Seedahmed S. Cao, Zheng Fu, Jianming Gu, Xudong Fang, Qiang Front Digit Health Digital Health Most post-stroke patients experience varying degrees of impairment in upper limb function and fine motor skills. Occupational therapy (OT) with other rehabilitation trainings is beneficial in improving the strength and dexterity of the impaired upper limb. An accurate upper limb assessment should be conducted before prescribing upper limb OT programs. In this paper, we present a novel multisensor method for the assessment of upper limb movements that uses kinematics and physiological sensors to capture the movement of the limbs and the surface electromyogram (sEMG). These sensors are Kinect, inertial measurement unit (IMU), Xsens, and sEMG. The key assessment features of the proposed model are as follows: (1) classification of OT exercises into four classes, (2) evaluation of the quality and completion of the OT exercises, and (3) evaluation of the relationship between upper limb mobility and muscle strength in patients. According to experimental results, the overall accuracy for OT-based motion classification is 82.2%. In addition, the fusing of Kinect and Xsens data reveals that muscle strength is highly correlated with the data with a correlation coefficient (CC) of 0.88. As a result of this research, occupational therapy specialists will be able to provide early support discharge, which could alleviate the problem of the great stress that the healthcare system is experiencing today. Frontiers Media S.A. 2021-12-17 /pmc/articles/PMC8718516/ /pubmed/34977858 http://dx.doi.org/10.3389/fdgth.2021.784120 Text en Copyright © 2021 Mahmoud, Cao, Fu, Gu and Fang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Digital Health Mahmoud, Seedahmed S. Cao, Zheng Fu, Jianming Gu, Xudong Fang, Qiang Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach |
title | Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach |
title_full | Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach |
title_fullStr | Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach |
title_full_unstemmed | Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach |
title_short | Occupational Therapy Assessment for Upper Limb Rehabilitation: A Multisensor-Based Approach |
title_sort | occupational therapy assessment for upper limb rehabilitation: a multisensor-based approach |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8718516/ https://www.ncbi.nlm.nih.gov/pubmed/34977858 http://dx.doi.org/10.3389/fdgth.2021.784120 |
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