中国组织工程研究

中国组织工程研究 ›› 2025, Vol. 29 ›› Issue (12): 2513-2520.doi: 10.12307/2025.392

• 肌肉肌腱韧带组织构建 tissue construction of the muscle, tendon and ligament • 上一篇    下一篇

下肢重复蹬伸至力竭过程中肌肉功能网络拓扑特性

张  陈1，冉令华2，3，呼慧敏2，3，张  欣2，3，周子健4，徐红旗1，史冀鹏1    

  1. 1东北师范大学体育学院运动能力测评与提升研究中心，吉林省长春市  130024；2中国标准化研究院人类工效学实验室，北京市  100191；3中国标准化研究院国家市场监管重点实验室(人因与工效学)，北京市  100820；4吉林大学仪器科学与电气工程学院，吉林省长春市  130061
  • 收稿日期:2024-04-25 接受日期:2024-06-11 出版日期:2025-04-28 发布日期:2024-09-10
  • 通讯作者: 徐红旗，博士，教授，博士生导师，东北师范大学体育学院运动能力测评与提升研究中心，吉林省长春市 130024
  • 作者简介:张陈，男，1999年生，安徽省合肥市人，汉族，东北师范大学体育学院在读硕士研究生，主要从事运动控制与生物力学研究。
  • 基金资助:
    国家重点研发计划(2023YFF0615902)，项目负责人：冉令华；国家市场监管重点实验室(人因与工效学)开放基金(2023SYSKF02002)，项目负责人：徐红旗；国家市场监管总局科技计划项目(2023MK192)，项目负责人：呼慧敏；中央基本科研业务费项目(522023Y-10381)，项目负责人：呼慧敏

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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摘要：




文题释义：
下肢蹬伸：一种复合负重训练，训练者通过双腿将重物或阻力推离自己，可用于评估下半身的整体力量(从臀大肌到小腿肌肉)，对于提高肢体灵活性和耐力具有重要作用。
肌肉功能网络：以肌肉为节点，肌肉之间的连接和相互作用关系强度为连线，构建功能网络，用于反映肌肉之间的协调变化。

背景：表面肌电已经被广泛用于监测肌肉疲劳，但传统肌电指标通常针对于单块肌肉，无法评价一组肌肉在疲劳过程中的变化。
目的：建立肌肉功能网络，提取复杂网络参数，研究不同疲劳程度下的肌肉功能网络拓扑特性变化，为疲劳的监测、预防提供理论和方法依据。
方法：11名受试者进行直到力竭的50% 1RM单腿下肢蹬伸运动，同步采集股直肌、股外侧肌、股内侧肌、股二头肌长头、胫骨前肌、腓肠肌外侧肌、腓肠肌内侧肌7块肌肉的肌电信号，以及心电信号和Borg CR-10量表评分；根据Borg CR-10量表评分划分为轻度、中度和重度三个疲劳阶段，采用心率和心率变异性验证疲劳阶段划分的有效性；以7块肌肉为节点，使用肌肉信号的相干性构建肌肉功能网络，提取聚类系数、平均加权度、全局效率、特征向量中心性4个复杂网络参数；提取肌电信号的均方值振幅、中位频率、瞬时平均频率和共激活比4种指标，并在3种疲劳程度下进行比较。
结果与结论：①3种疲劳阶段在心率及心率变异性上产生显著性差异，证明了疲劳阶段划分的有效性；②对于不同肌肉在3种疲劳程度下的肌电指标：均方值振幅和共激活比未表现出差异，中位频率在股外侧肌、股内侧肌和股二头肌长头表现出稳健的疲劳趋势，瞬时平均频率则在股直肌、股外侧肌、股内侧肌和股二头肌长头表现出稳健的疲劳趋势；瞬时平均频率的性能优于中位频率和均方值振幅，但三者仅在主要工作肌群能够获得较好的稳健趋势，共激活比不受疲劳因素的影响；③股外侧肌-股内侧肌、股外侧肌-股二头肌长头、股外侧肌-腓肠肌内侧肌和股内侧肌-股二头肌长头连接强度逐渐增加，平均加权度、聚类系数和全局效率在疲劳后表现出显著差异，并且与疲劳程度之间显著相关。结果表明：肌肉功能网络内的连通强度变化能够反映疲劳过程中肌肉间的协同性和互补性；聚类系数、平均加权度、全局效率可作为一组肌肉疲劳的监测指标。
https://orcid.org/0009-0009-8897-9340(张陈)

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

关键词: 肌肉功能网络, 下肢蹬伸, 膝关节, 肌电, Borg CR-10量表, 疲劳, 运动损伤, 复杂网络指标, 相干性

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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