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Integrated System for Monitoring Muscular States during Elbow Flexor Resistance Training in Bedridden Patients
To improve or maintain the physical function of bedridden patients, appropriate and effective exercises are required during the patient's bed rest. Resistance training (RT) is an effective exercise for improving the physical function of bedridden patients, and the improvement of the physical fu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360054/ https://www.ncbi.nlm.nih.gov/pubmed/30800256 http://dx.doi.org/10.1155/2019/4290957 |
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author | Xu, Taojin Jiang, Zhongwei Jeong, Jongyeob Morita, Minoru Xu, Hongbin |
author_facet | Xu, Taojin Jiang, Zhongwei Jeong, Jongyeob Morita, Minoru Xu, Hongbin |
author_sort | Xu, Taojin |
collection | PubMed |
description | To improve or maintain the physical function of bedridden patients, appropriate and effective exercises are required during the patient's bed rest. Resistance training (RT) is an effective exercise for improving the physical function of bedridden patients, and the improvement of the physical function is caused by mechanical stimuli associated with RT. Currently, the measured mechanical stimuli are external variables which represent the synthetic effect of multiple muscles and body movements. Important features of stimuli experienced by muscles are of crucial importance in explaining muscular strength and power adaptation. This study describes an integrated system for assessing muscular states during elbow flexor resistance training in bedridden patients, and some experiments were carried out to test and evaluate this system. The integrated system incorporates an elbow joint angle estimation model (EJAEM), a musculoskeletal model (MSM), and a muscle-tendon model. The EJAEM enables real-time interaction between patient and MSM. The MSM is a three-dimensional model of the upper extremity, including major muscles that make up the elbow flexor and extensor, and was built based on public data. One set of concentric and eccentric contraction was performed by a healthy subject, and the results of the calculations were analyzed to show important features of mechanical stimuli experienced by muscles during the training. The integrated system provides a considerable method to monitor the body-level and muscle-level mechanical stimuli during elbow flexor resistance training in bedridden patients. |
format | Online Article Text |
id | pubmed-6360054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-63600542019-02-24 Integrated System for Monitoring Muscular States during Elbow Flexor Resistance Training in Bedridden Patients Xu, Taojin Jiang, Zhongwei Jeong, Jongyeob Morita, Minoru Xu, Hongbin J Healthc Eng Research Article To improve or maintain the physical function of bedridden patients, appropriate and effective exercises are required during the patient's bed rest. Resistance training (RT) is an effective exercise for improving the physical function of bedridden patients, and the improvement of the physical function is caused by mechanical stimuli associated with RT. Currently, the measured mechanical stimuli are external variables which represent the synthetic effect of multiple muscles and body movements. Important features of stimuli experienced by muscles are of crucial importance in explaining muscular strength and power adaptation. This study describes an integrated system for assessing muscular states during elbow flexor resistance training in bedridden patients, and some experiments were carried out to test and evaluate this system. The integrated system incorporates an elbow joint angle estimation model (EJAEM), a musculoskeletal model (MSM), and a muscle-tendon model. The EJAEM enables real-time interaction between patient and MSM. The MSM is a three-dimensional model of the upper extremity, including major muscles that make up the elbow flexor and extensor, and was built based on public data. One set of concentric and eccentric contraction was performed by a healthy subject, and the results of the calculations were analyzed to show important features of mechanical stimuli experienced by muscles during the training. The integrated system provides a considerable method to monitor the body-level and muscle-level mechanical stimuli during elbow flexor resistance training in bedridden patients. Hindawi 2019-01-17 /pmc/articles/PMC6360054/ /pubmed/30800256 http://dx.doi.org/10.1155/2019/4290957 Text en Copyright © 2019 Taojin Xu et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Xu, Taojin Jiang, Zhongwei Jeong, Jongyeob Morita, Minoru Xu, Hongbin Integrated System for Monitoring Muscular States during Elbow Flexor Resistance Training in Bedridden Patients |
title | Integrated System for Monitoring Muscular States during Elbow Flexor Resistance Training in Bedridden Patients |
title_full | Integrated System for Monitoring Muscular States during Elbow Flexor Resistance Training in Bedridden Patients |
title_fullStr | Integrated System for Monitoring Muscular States during Elbow Flexor Resistance Training in Bedridden Patients |
title_full_unstemmed | Integrated System for Monitoring Muscular States during Elbow Flexor Resistance Training in Bedridden Patients |
title_short | Integrated System for Monitoring Muscular States during Elbow Flexor Resistance Training in Bedridden Patients |
title_sort | integrated system for monitoring muscular states during elbow flexor resistance training in bedridden patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360054/ https://www.ncbi.nlm.nih.gov/pubmed/30800256 http://dx.doi.org/10.1155/2019/4290957 |
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