Table 1_Characterization of muscle synergy similarity and adaptation in hip exoskeleton-assisted locomotion.docx
<p>Recent advancements in robotic exoskeleton technology have demonstrated significant potential in reducing users’ energy consumption and muscle activation. However, how users adjust muscle recruitment and coordination in expenditure and muscle activation levels. However, the mechanisms under...
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2025
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| Summary: | <p>Recent advancements in robotic exoskeleton technology have demonstrated significant potential in reducing users’ energy consumption and muscle activation. However, how users adjust muscle recruitment and coordination in expenditure and muscle activation levels. However, the mechanisms underlying users’ adaptation of muscle recruitment and coordination patterns in response to external robotic assistance remain poorly understood. This study introduces a novel methodological framework for quantifying the impact of assistance on human muscle synergy patterns through similarity analysis, which incorporates a weighted summation of Pearson correlation coefficients between paired synergies. Eight healthy adult participats underwent treadmill walking trials under two conditions: with and without a portable hip exoskeleton. The experimental protocol consisted of two distinct sessions. In the first session, participants walked with varying assistive torque, enabling comparative analysis of muscle synergies across different conditions. The second session, involved a temporal adaptation assessment, where participants initially walked in a 2-min zero torque (ZT) mode, followed by a 10-min assistive mode, and concluded with another 2-min ZT mode. The analysis revealed that four primary synergies accounted for 92.73% ± 0.43% and 93.06% ± 0.64% of the variance in surface electromyography (sEMG) signals during exoskeleton-assisted and unassisted walking, respectively. The developed similarity indices proved effective in quantifying significance differences in muscle synergy patterns between assisted and unassisted conditions. These findings provide valuable insights into neuromuscular control mechanisms during exoskeleton-assisted locomotion, contributing to the optimization of robotic assistance strategies.</p> |
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