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Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors

BACKGROUND: Muscle synergies are now widely discussed as a method for evaluating the existence of redundant neural networks that can be activated to enhance stroke rehabilitation. However, this approach was initially conceived to study muscle coordination during learned motions in healthy individual...

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Autores principales: Costa-García, Álvaro, Ozaki, Ken-ichi, Yamasaki, Hiroshi, Itkonen, Matti, S., Fady Alnajjar, Okajima, Shotaro, Tanimoto, Masanori, Kondo, Izumi, Shimoda, Shingo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6829968/
https://www.ncbi.nlm.nih.gov/pubmed/31684980
http://dx.doi.org/10.1186/s12984-019-0611-z
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author Costa-García, Álvaro
Ozaki, Ken-ichi
Yamasaki, Hiroshi
Itkonen, Matti
S., Fady Alnajjar
Okajima, Shotaro
Tanimoto, Masanori
Kondo, Izumi
Shimoda, Shingo
author_facet Costa-García, Álvaro
Ozaki, Ken-ichi
Yamasaki, Hiroshi
Itkonen, Matti
S., Fady Alnajjar
Okajima, Shotaro
Tanimoto, Masanori
Kondo, Izumi
Shimoda, Shingo
author_sort Costa-García, Álvaro
collection PubMed
description BACKGROUND: Muscle synergies are now widely discussed as a method for evaluating the existence of redundant neural networks that can be activated to enhance stroke rehabilitation. However, this approach was initially conceived to study muscle coordination during learned motions in healthy individuals. After brain damage, there are several neural adaptations that contribute to the recovery of motor strength, with muscle coordination being one of them. In this study, a model is proposed that assesses motion based on surface electromyography (sEMG) according to two main factors closely related to the neural adaptations underlying motor recovery: (1) the correct coordination of the muscles involved in a particular motion and (2) the ability to tune the effective strength of each muscle through muscle fiber contractions. These two factors are hypothesized to be affected differently by brain damage. Therefore, their independent evaluation will play an important role in understanding the origin of stroke-related motor impairments. RESULTS: The model proposed was validated by analyzing sEMG data from 18 stroke patients with different paralysis levels and 30 healthy subjects. While the factors necessary to describe motion were stable across heathy subjects, there was an increasing disassociation for stroke patients with severe motor impairment. CONCLUSIONS: The clear dissociation between the coordination of muscles and the tuning of their strength demonstrates the importance of evaluating these factors in order to choose appropriate rehabilitation therapies. The model described in this research provides an efficient approach to promptly evaluate these factors through the use of two intuitive indexes.
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spelling pubmed-68299682019-11-08 Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors Costa-García, Álvaro Ozaki, Ken-ichi Yamasaki, Hiroshi Itkonen, Matti S., Fady Alnajjar Okajima, Shotaro Tanimoto, Masanori Kondo, Izumi Shimoda, Shingo J Neuroeng Rehabil Methodology BACKGROUND: Muscle synergies are now widely discussed as a method for evaluating the existence of redundant neural networks that can be activated to enhance stroke rehabilitation. However, this approach was initially conceived to study muscle coordination during learned motions in healthy individuals. After brain damage, there are several neural adaptations that contribute to the recovery of motor strength, with muscle coordination being one of them. In this study, a model is proposed that assesses motion based on surface electromyography (sEMG) according to two main factors closely related to the neural adaptations underlying motor recovery: (1) the correct coordination of the muscles involved in a particular motion and (2) the ability to tune the effective strength of each muscle through muscle fiber contractions. These two factors are hypothesized to be affected differently by brain damage. Therefore, their independent evaluation will play an important role in understanding the origin of stroke-related motor impairments. RESULTS: The model proposed was validated by analyzing sEMG data from 18 stroke patients with different paralysis levels and 30 healthy subjects. While the factors necessary to describe motion were stable across heathy subjects, there was an increasing disassociation for stroke patients with severe motor impairment. CONCLUSIONS: The clear dissociation between the coordination of muscles and the tuning of their strength demonstrates the importance of evaluating these factors in order to choose appropriate rehabilitation therapies. The model described in this research provides an efficient approach to promptly evaluate these factors through the use of two intuitive indexes. BioMed Central 2019-11-04 /pmc/articles/PMC6829968/ /pubmed/31684980 http://dx.doi.org/10.1186/s12984-019-0611-z Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Costa-García, Álvaro
Ozaki, Ken-ichi
Yamasaki, Hiroshi
Itkonen, Matti
S., Fady Alnajjar
Okajima, Shotaro
Tanimoto, Masanori
Kondo, Izumi
Shimoda, Shingo
Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors
title Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors
title_full Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors
title_fullStr Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors
title_full_unstemmed Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors
title_short Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors
title_sort model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6829968/
https://www.ncbi.nlm.nih.gov/pubmed/31684980
http://dx.doi.org/10.1186/s12984-019-0611-z
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