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Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator
Stroke has been the leading cause of disability due to the induced spasticity in the upper extremity. The constant flexion of spastic fingers following stroke has not been well described. Accurate measurements for joint stiffness help clinicians have a better access to the level of impairment after...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775510/ https://www.ncbi.nlm.nih.gov/pubmed/33392166 http://dx.doi.org/10.3389/fbioe.2020.592637 |
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author | Shi, Xiang Qian Heung, Ho Lam Tang, Zhi Qiang Tong, Kai Yu Li, Zheng |
author_facet | Shi, Xiang Qian Heung, Ho Lam Tang, Zhi Qiang Tong, Kai Yu Li, Zheng |
author_sort | Shi, Xiang Qian |
collection | PubMed |
description | Stroke has been the leading cause of disability due to the induced spasticity in the upper extremity. The constant flexion of spastic fingers following stroke has not been well described. Accurate measurements for joint stiffness help clinicians have a better access to the level of impairment after stroke. Previously, we conducted a method for quantifying the passive finger joint stiffness based on the pressure-angle relationship between the spastic fingers and the soft-elastic composite actuator (SECA). However, it lacks a ground-truth to demonstrate the compatibility between the SECA-facilitated stiffness estimation and standard joint stiffness quantification procedure. In this study, we compare the passive metacarpophalangeal (MCP) joint stiffness measured using the SECA with the results from our designed standalone mechatronics device, which measures the passive metacarpophalangeal joint torque and angle during passive finger rotation. Results obtained from the fitting model that concludes the stiffness characteristic are further compared with the results obtained from SECA-Finger model, as well as the clinical score of Modified Ashworth Scale (MAS) for grading spasticity. These findings suggest the possibility of passive MCP joint stiffness quantification using the soft robotic actuator during the performance of different tasks in hand rehabilitation. |
format | Online Article Text |
id | pubmed-7775510 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77755102021-01-02 Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator Shi, Xiang Qian Heung, Ho Lam Tang, Zhi Qiang Tong, Kai Yu Li, Zheng Front Bioeng Biotechnol Bioengineering and Biotechnology Stroke has been the leading cause of disability due to the induced spasticity in the upper extremity. The constant flexion of spastic fingers following stroke has not been well described. Accurate measurements for joint stiffness help clinicians have a better access to the level of impairment after stroke. Previously, we conducted a method for quantifying the passive finger joint stiffness based on the pressure-angle relationship between the spastic fingers and the soft-elastic composite actuator (SECA). However, it lacks a ground-truth to demonstrate the compatibility between the SECA-facilitated stiffness estimation and standard joint stiffness quantification procedure. In this study, we compare the passive metacarpophalangeal (MCP) joint stiffness measured using the SECA with the results from our designed standalone mechatronics device, which measures the passive metacarpophalangeal joint torque and angle during passive finger rotation. Results obtained from the fitting model that concludes the stiffness characteristic are further compared with the results obtained from SECA-Finger model, as well as the clinical score of Modified Ashworth Scale (MAS) for grading spasticity. These findings suggest the possibility of passive MCP joint stiffness quantification using the soft robotic actuator during the performance of different tasks in hand rehabilitation. Frontiers Media S.A. 2020-12-18 /pmc/articles/PMC7775510/ /pubmed/33392166 http://dx.doi.org/10.3389/fbioe.2020.592637 Text en Copyright © 2020 Shi, Heung, Tang, Tong and Li. http://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 | Bioengineering and Biotechnology Shi, Xiang Qian Heung, Ho Lam Tang, Zhi Qiang Tong, Kai Yu Li, Zheng Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator |
title | Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator |
title_full | Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator |
title_fullStr | Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator |
title_full_unstemmed | Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator |
title_short | Verification of Finger Joint Stiffness Estimation Method With Soft Robotic Actuator |
title_sort | verification of finger joint stiffness estimation method with soft robotic actuator |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775510/ https://www.ncbi.nlm.nih.gov/pubmed/33392166 http://dx.doi.org/10.3389/fbioe.2020.592637 |
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