Quantifying lower-limb muscle coordination during cycling using electromyography-informed muscle synergies
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915410631196672 |
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| author | Ahmadi, Reza Rasoulian, Shahram Heidary, Hamidreza Aboodarda, Saied Jalal Uchida, Thomas K. Herzog, Walter Komeili, Amin |
| author_facet | Ahmadi, Reza Rasoulian, Shahram Heidary, Hamidreza Aboodarda, Saied Jalal Uchida, Thomas K. Herzog, Walter Komeili, Amin |
| contents | Assessment of muscle coordination during cycling may provide insight into motor control strategies and movement efficiency. This study evaluated muscle synergies and coactivation patterns as indicators of neuromuscular coordination in lower-limb across three power levels of cycling. Twenty recreational cyclists performed a graded cycling test on a stationary bicycle ergometer. Electromyography was recorded bilaterally from seven lower-limb muscles and muscle synergies were extracted using non-negative matrix factorization. The Coactivation Index (CI), Synergy Index (SI), and Synergy Coordination Index (SCI) were calculated to assess muscle coordination patterns. Four muscle synergies were identified consistently across power levels, with changes in synergy composition and activation timing correlated with increased muscular demands. As power level increased, the CI showed reduced muscle coactivation at the knee and greater muscle coactivation at the ankle. The SI revealed a greater contribution of the synergy weights of the extensor muscles than those of the flexor muscles at the knee. In contrast, the relative EMG contribution of hip extensor and flexor muscles remained consistent with increasing power levels. The SCI increased significantly with increasing power level, suggesting a reduction in the size of the synergy space and improved neuromuscular coordination. These findings provide insight into how the central nervous system modulates its response to increasing mechanical demands. Combining synergy and coactivation indices offers a promising approach to assess motor control, inform rehabilitation, and optimize performance in cycling tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_19637 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Quantifying lower-limb muscle coordination during cycling using electromyography-informed muscle synergies Ahmadi, Reza Rasoulian, Shahram Heidary, Hamidreza Aboodarda, Saied Jalal Uchida, Thomas K. Herzog, Walter Komeili, Amin Medical Physics Quantitative Methods Assessment of muscle coordination during cycling may provide insight into motor control strategies and movement efficiency. This study evaluated muscle synergies and coactivation patterns as indicators of neuromuscular coordination in lower-limb across three power levels of cycling. Twenty recreational cyclists performed a graded cycling test on a stationary bicycle ergometer. Electromyography was recorded bilaterally from seven lower-limb muscles and muscle synergies were extracted using non-negative matrix factorization. The Coactivation Index (CI), Synergy Index (SI), and Synergy Coordination Index (SCI) were calculated to assess muscle coordination patterns. Four muscle synergies were identified consistently across power levels, with changes in synergy composition and activation timing correlated with increased muscular demands. As power level increased, the CI showed reduced muscle coactivation at the knee and greater muscle coactivation at the ankle. The SI revealed a greater contribution of the synergy weights of the extensor muscles than those of the flexor muscles at the knee. In contrast, the relative EMG contribution of hip extensor and flexor muscles remained consistent with increasing power levels. The SCI increased significantly with increasing power level, suggesting a reduction in the size of the synergy space and improved neuromuscular coordination. These findings provide insight into how the central nervous system modulates its response to increasing mechanical demands. Combining synergy and coactivation indices offers a promising approach to assess motor control, inform rehabilitation, and optimize performance in cycling tasks. |
| title | Quantifying lower-limb muscle coordination during cycling using electromyography-informed muscle synergies |
| topic | Medical Physics Quantitative Methods |
| url | https://arxiv.org/abs/2507.19637 |