Chinese Journal of Tissue Engineering Research ›› 2025, Vol. 29 ›› Issue (12): 2513-2520.doi: 10.12307/2025.392

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Topological characteristics of muscle functional networks during repeated leg press to exhaustion

Zhang Chen1, Ran Linghua2, 3, Hu Huimin2, 3, Zhang Xin2, 3, Zhou Zijian4, Xu Hongqi1, Shi Jipeng1   

  1. 1Research Centre for Assessment and Enhancement of Athletic Ability, School of Physical Education and Sports, Northeast Normal University, Changchun 130024, Jilin Province, China; 2Ergonomics Laboratory, China National Institute of Standardization, Beijing 100191, China; 3SAMR Key Laboratory of Human Factors and Ergonomics, China National Institute of Standardization, Beijing 100820, China; 4School of Instrumentation Science and Electrical Engineering, Jilin University, Changchun 130061, Jilin Province, China
  • Received:2024-04-25 Accepted:2024-06-11 Online:2025-04-28 Published:2024-09-10
  • Contact: Xu Hongqi, PhD, Professor, Doctoral supervisor, Research Centre for Assessment and Enhancement of Athletic Ability, School of Physical Education and Sports, Northeast Normal University, Changchun 130024, Jilin Province, China
  • About author:Zhang Chen, Master candidate, Research Centre for Assessment and Enhancement of Athletic Ability, School of Physical Education and Sports, Northeast Normal University, Changchun 130024, Jilin Province, China
  • Supported by:
    National Key R&D Program of China, No. 2023YFF0615902 (to RLH); Open Fund of the Key Laboratory of Human Factors and Ergonomics for State Market Regulation, No. 2023SYSKF02002 (to XHQ); Technology Plan Project of State Administration for Market Regulation, No. 2023MK192 (to HHM); the Fundamental Research Funds for the Central Universities, No. 522023Y-10381 (to HHM)

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Abstract: BACKGROUND: Surface electromyography has been extensively utilized for monitoring muscle fatigue. However, traditional electromyographic metrics typically focus on individual muscles and fail to assess the variations in a muscle group during the fatigue process.
OBJECTIVE: To establish a muscle functional network to extract complex network parameters and investigate the topological property changes of the muscle functional network under different levels of fatigue, aiming to provide theoretical and methodological foundations for fatigue monitoring and prevention. 
METHODS: Eleven participants performed single-leg leg press exercise at 50% of one-repetition maximum until exhaustion. Simultaneously, electromyographic signals of seven muscles (rectus femoris, vastus lateralis, vastus medialis, biceps femoris, tibialis anterior, lateral gastrocnemius, and medial gastrocnemius), electrocardiographic signals, and Borg CR-10 scale scores were collected. The Borg CR-10 scale was used to categorize three fatigue stages: mild, moderate, and severe. Heart rate and heart rate variability were calculated to validate the effective division of fatigue stages. Using the coherence of muscle signals, a muscle functional network was constructed with the seven muscles as nodes, and four complex network parameters (clustering coefficient, average weighted degree, global efficiency, and eigenvector centrality) were extracted. Additionally, four electromyographic indices (root mean square, median frequency, instantaneous mean frequency, and co-activation ratio) were extracted and compared under the three levels of fatigue. 
RESULTS AND CONCLUSION: (1) Differences in heart rate and heart rate variability were observed across three fatigue stages, indicating the effectiveness of fatigue stage delineation. (2) Electromyographic indicators for different muscles under three levels of fatigue: root mean square and co-activation ratio showed no differences; however, median frequency exhibited robust fatigue trends in vastus lateralis, vastus medialis, and biceps femoris, while instantaneous mean frequency demonstrated robust fatigue trends in rectus femoris, vastus lateralis, vastus medialis, and biceps femoris. Instantaneous mean frequency outperformed median frequency and root mean square, yet all three indicators showed robust trends only for the major working muscle groups, unaffected by fatigue factors, unlike the co-activation ratio. (3) The connectivity strength between vastus lateralis and vastus medialis, vastus lateralis and biceps femoris, vastus lateralis and gastrocnemius medialis, and vastus medialis and biceps femoris gradually increased, showing significant differences in average weighted degree, clustering coefficient, and global efficiency post-fatigue, significantly correlated with fatigue levels. To conclude, changes in connectivity strength reflect the synergy and complementarity among muscles during fatigue. Clustering coefficient, average weighted degree, and global efficiency serve as fatigue markers reflecting overall muscle changes.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words: muscle function network, leg press, knee joint, electromyography, Borg CR-10 Scale, fatigue, sports injury, complex network indicator, coherence

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