Journal
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 69, Issue 10, Pages 3119-3130Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2022.3161726
Keywords
Muscles; Stroke (medical condition); Spatiotemporal phenomena; Feature extraction; Indexes; Band-pass filters; Aerospace electronics; Motor function quantification; muscle synergy space model; post-stroke; rehabilitation
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Funding
- National Natural Science Foundation of China [61733011]
- Guangdong Science and Technology Research Council [2020B1515120064]
- Shenzhen Basic Research Key Program [JCYJ20210324120214040]
- GuangCi Professorship Program of Ruijin Hospital Shanghai Jiao Tong University School of Medicine
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This study presents a new assessment method based on the muscle synergy space (MSS) model to evaluate motor functions after stroke. By analyzing the spatial and temporal characteristics of muscle synergies, this method provides more scientific rehabilitation guidance.
The muscle synergy hypothesis assumes that the nervous system controls muscles in groups to simplify behavioral tasks, which makes it possible for modularizing motor function assessment. This paper presents a new assessment method based on muscle synergy space (MSS) model to evaluate motor functions after stroke. It consists of spatiotemporal feature module, muscle activation module and synergy activation module, and focuses on the spatial and temporal characteristics of muscle synergies via synergy vectors and activation coefficients. We further applied this method to reveal spatial and temporal characteristics difference of muscle synergy between healthy controls and stroke patients. The effectiveness and accuracy of MSS model were proved by significant positive correlations between Fugl-Meyer score and the total number of optimal synergies of three modules. This measurement methodology could serve as a quantitative indicator for motor function and provide more scientific rehabilitation guidance.
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