Journal
BIOMIMETICS
Volume 6, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/biomimetics6040063
Keywords
inter-subject; intra-subject; muscle synergies; reaching movements; upper limb; variability
Funding
- National Natural Science Foundation of China [51775108]
- Natural Science Foundation of Jiangsu Province [BK20190368]
- Fundamental Research Funds for the Central Universities [KYCX19_0061]
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The study assesses intra-subject and inter-subject variability in multi-directional reaching movements using muscle synergies, revealing lower intra-subject variability than inter-subject variability and confirming shared underlying control structures. Muscle synergies are found to be a valuable tool for quantifying variability at the muscle level, with both intra-subject and inter-subject similarity higher than random matching. The study deepens understanding of muscle synergy-based motor function assessment and rehabilitation applications, highlighting their applicability to real scenarios.
Quantifying movement variability is a crucial aspect for clinical and laboratory investigations in several contexts. However, very few studies have assessed, in detail, the intra-subject variability across movements and the inter-subject variability. Muscle synergies are a valuable method that can be used to assess such variability. In this study, we assess, in detail, intra-subject and inter-subject variability in a scenario based on a comprehensive dataset, including multiple repetitions of multi-directional reaching movements. The results show that muscle synergies are a valuable tool for quantifying variability at the muscle level and reveal that intra-subject variability is lower than inter-subject variability in synergy modules and related temporal coefficients, and both intra-subject and inter-subject similarity are higher than random synergy matching, confirming shared underlying control structures. The study deepens the available knowledge on muscle synergy-based motor function assessment and rehabilitation applications, discussing their applicability to real scenarios.
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