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Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot
Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor function in stroke patients. However, most current rehabilitation robotic controllers will provide too much assistance force and focus only on the patient’s position tracking performance while ignoring the...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10146308/ https://www.ncbi.nlm.nih.gov/pubmed/37112385 http://dx.doi.org/10.3390/s23084042 |
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author | Hu, Yang Meng, Jingyan Li, Guoning Zhao, Dazheng Feng, Guang Zuo, Guokun Liu, Yunfeng Zhang, Jiaji Shi, Changcheng |
author_facet | Hu, Yang Meng, Jingyan Li, Guoning Zhao, Dazheng Feng, Guang Zuo, Guokun Liu, Yunfeng Zhang, Jiaji Shi, Changcheng |
author_sort | Hu, Yang |
collection | PubMed |
description | Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor function in stroke patients. However, most current rehabilitation robotic controllers will provide too much assistance force and focus only on the patient’s position tracking performance while ignoring the patient’s interactive force situation, resulting in the inability to accurately assess the patient’s true motor intention and difficulty stimulating the patient’s initiative, thus negatively affecting the patient’s rehabilitation outcome. Therefore, this paper proposes a fuzzy adaptive passive (FAP) control strategy based on subjects’ task performance and impulse. To ensure the safety of subjects, a passive controller based on the potential field is designed to guide and assist patients in their movements, and the stability of the controller is demonstrated in a passive formalism. Then, using the subject’s task performance and impulse as evaluation indicators, fuzzy logic rules were designed and used as an evaluation algorithm to quantitively assess the subject’s motor ability and to adaptively modify the stiffness coefficient of the potential field and thus change the magnitude of the assistance force to stimulate the subject’s initiative. Through experiments, this control strategy has been shown to not only improve the subject’s initiative during the training process and ensure their safety during training but also enhance the subject’s motor learning ability. |
format | Online Article Text |
id | pubmed-10146308 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101463082023-04-29 Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot Hu, Yang Meng, Jingyan Li, Guoning Zhao, Dazheng Feng, Guang Zuo, Guokun Liu, Yunfeng Zhang, Jiaji Shi, Changcheng Sensors (Basel) Article Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor function in stroke patients. However, most current rehabilitation robotic controllers will provide too much assistance force and focus only on the patient’s position tracking performance while ignoring the patient’s interactive force situation, resulting in the inability to accurately assess the patient’s true motor intention and difficulty stimulating the patient’s initiative, thus negatively affecting the patient’s rehabilitation outcome. Therefore, this paper proposes a fuzzy adaptive passive (FAP) control strategy based on subjects’ task performance and impulse. To ensure the safety of subjects, a passive controller based on the potential field is designed to guide and assist patients in their movements, and the stability of the controller is demonstrated in a passive formalism. Then, using the subject’s task performance and impulse as evaluation indicators, fuzzy logic rules were designed and used as an evaluation algorithm to quantitively assess the subject’s motor ability and to adaptively modify the stiffness coefficient of the potential field and thus change the magnitude of the assistance force to stimulate the subject’s initiative. Through experiments, this control strategy has been shown to not only improve the subject’s initiative during the training process and ensure their safety during training but also enhance the subject’s motor learning ability. MDPI 2023-04-17 /pmc/articles/PMC10146308/ /pubmed/37112385 http://dx.doi.org/10.3390/s23084042 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hu, Yang Meng, Jingyan Li, Guoning Zhao, Dazheng Feng, Guang Zuo, Guokun Liu, Yunfeng Zhang, Jiaji Shi, Changcheng Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot |
title | Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot |
title_full | Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot |
title_fullStr | Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot |
title_full_unstemmed | Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot |
title_short | Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot |
title_sort | fuzzy adaptive passive control strategy design for upper-limb end-effector rehabilitation robot |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10146308/ https://www.ncbi.nlm.nih.gov/pubmed/37112385 http://dx.doi.org/10.3390/s23084042 |
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