Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research

Background/Objective: Muscle synergy analysis based on machine learning has significantly advanced our understanding of the mechanisms underlying the central nervous system motor control of gait and has identified abnormal gait synergies in stroke patients through various analytical approaches. Howe...

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Main Authors: Jaehyuk Lee, Kimyung Kim, Youngchae Cho, Hyeongdong Kim
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Neurology International
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Online Access:https://www.mdpi.com/2035-8377/16/6/108
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author Jaehyuk Lee
Kimyung Kim
Youngchae Cho
Hyeongdong Kim
author_facet Jaehyuk Lee
Kimyung Kim
Youngchae Cho
Hyeongdong Kim
author_sort Jaehyuk Lee
collection DOAJ
description Background/Objective: Muscle synergy analysis based on machine learning has significantly advanced our understanding of the mechanisms underlying the central nervous system motor control of gait and has identified abnormal gait synergies in stroke patients through various analytical approaches. However, discrepancies in experimental conditions and computational methods have limited the clinical application of these findings. This review seeks to integrate the results of existing studies on the features of muscle synergies in stroke-related gait abnormalities and provide clinical and research insights into gait rehabilitation. Methods: A systematic search of Web of Science, PubMed, and Scopus was conducted, yielding 10 full-text articles for inclusion. Results: By comprehensively reviewing the consistencies and differences in the study outcomes, we emphasize the need to segment the gait cycle into specific phases (e.g., weight acceptance, push-off, foot clearance, and leg deceleration) during the treatment process of gait rehabilitation and to develop rehabilitation protocols aimed at restoring normal synergy patterns in each gait phase and fractionating reduced synergies. Conclusions: Future research should focus on validating these protocols to improve clinical outcomes and introducing indicators to assess abnormalities in the temporal features of muscle synergies.
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spelling doaj-art-d78552ca094e43858333fb87975abdf32025-08-20T02:56:59ZengMDPI AGNeurology International2035-83772024-11-011661451146310.3390/neurolint16060108Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future ResearchJaehyuk Lee0Kimyung Kim1Youngchae Cho2Hyeongdong Kim3Smart Technology Laboratory, Kongju National University, Cheonan-si 31080, Republic of KoreaDepartment of Physical Therapy, School of Health and Environmental Science, College of Health Science, Korea University, Seoul 02841, Republic of KoreaDepartment of Physical Therapy, School of Health and Environmental Science, College of Health Science, Korea University, Seoul 02841, Republic of KoreaDepartment of Physical Therapy, School of Health and Environmental Science, College of Health Science, Korea University, Seoul 02841, Republic of KoreaBackground/Objective: Muscle synergy analysis based on machine learning has significantly advanced our understanding of the mechanisms underlying the central nervous system motor control of gait and has identified abnormal gait synergies in stroke patients through various analytical approaches. However, discrepancies in experimental conditions and computational methods have limited the clinical application of these findings. This review seeks to integrate the results of existing studies on the features of muscle synergies in stroke-related gait abnormalities and provide clinical and research insights into gait rehabilitation. Methods: A systematic search of Web of Science, PubMed, and Scopus was conducted, yielding 10 full-text articles for inclusion. Results: By comprehensively reviewing the consistencies and differences in the study outcomes, we emphasize the need to segment the gait cycle into specific phases (e.g., weight acceptance, push-off, foot clearance, and leg deceleration) during the treatment process of gait rehabilitation and to develop rehabilitation protocols aimed at restoring normal synergy patterns in each gait phase and fractionating reduced synergies. Conclusions: Future research should focus on validating these protocols to improve clinical outcomes and introducing indicators to assess abnormalities in the temporal features of muscle synergies.https://www.mdpi.com/2035-8377/16/6/108gaitmuscle synergymotor modulerehabilitationstroke
spellingShingle Jaehyuk Lee
Kimyung Kim
Youngchae Cho
Hyeongdong Kim
Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research
Neurology International
gait
muscle synergy
motor module
rehabilitation
stroke
title Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research
title_full Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research
title_fullStr Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research
title_full_unstemmed Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research
title_short Application of Muscle Synergies for Gait Rehabilitation After Stroke: Implications for Future Research
title_sort application of muscle synergies for gait rehabilitation after stroke implications for future research
topic gait
muscle synergy
motor module
rehabilitation
stroke
url https://www.mdpi.com/2035-8377/16/6/108
work_keys_str_mv AT jaehyuklee applicationofmusclesynergiesforgaitrehabilitationafterstrokeimplicationsforfutureresearch
AT kimyungkim applicationofmusclesynergiesforgaitrehabilitationafterstrokeimplicationsforfutureresearch
AT youngchaecho applicationofmusclesynergiesforgaitrehabilitationafterstrokeimplicationsforfutureresearch
AT hyeongdongkim applicationofmusclesynergiesforgaitrehabilitationafterstrokeimplicationsforfutureresearch