Electroencephalogram (EEG) and electromyogram (EMG) signals during motion control reflect the interaction between the cortex and muscle. Therefore, dynamic information regarding the cortical-muscle system is of significance for the evaluation of muscle fatigue. We treated the cortex and muscle as a whole system and then applied graph theory and symbolic transfer entropy to establish an effective cortical-muscle network in the beta band (12–30 Hz) and the gamma band (30–45 Hz). Ten healthy volunteers were recruited to participate in the isometric contraction at the level of 30% maximal voluntary contraction. Pre- and post-fatigue EEG and EMG data were recorded. According to the Borg scale, only data with an index greater than 14 less than 19 were selected as fatigue data. The results show that after muscle fatigue: (1) the decrease in the force-generating capacity leads to an increase in STE of the cortical-muscle system; (2) increases of dynamic forces in fatigue leads to a shift from the beta band to gamma band in the activity of the cortical-muscle network; (3) the areas of the frontal and parietal lobes involved in muscle activation within the ipsilateral hemibrain have a compensatory role. Classification based on support vector machine algorithm showed that the accuracy is improved compared to the brain network. These results illustrate the regulation mechanism of the cortical-muscle system during the development of muscle fatigue, and reveal the great potential of the cortical-muscle network in analyzing motor tasks.

运动控制期间的脑电图 (EEG) 和肌电图 (EMG) 信号反映了皮层和肌肉之间的相互作用。因此，关于皮层肌肉系统的动态信息对于肌肉疲劳的评估具有重要意义。我们将皮层和肌肉视为一个整体系统，然后应用图论和符号传递熵在 beta 波段（12-30 Hz）和 gamma 波段（30-45 Hz）建立有效的皮层肌肉网络。招募了 10 名健康志愿者以最大自愿收缩 30% 的水平参与等长收缩。记录疲劳前后的 EEG 和 EMG 数据。根据 Borg 量表，仅选择指数大于 14 小于 19 的数据作为疲劳数据。结果表明，肌肉疲劳后：(1) 生力能力的下降导致皮质-肌肉系统的 STE 增加；(2) 疲劳中动态力的增加导致皮质-肌肉网络活动从 β 波段转移到 γ 波段；(3)同侧半脑内参与肌肉激活的额叶和顶叶区域具有代偿作用。基于支持向量机算法的分类表明，与脑网络相比，准确率有所提高。这些结果说明了皮层肌肉系统在肌肉疲劳发展过程中的调节机制，并揭示了皮层肌肉网络在分析运动任务方面的巨大潜力。(2) 疲劳中动态力的增加导致皮质-肌肉网络活动从 β 波段转移到 γ 波段；(3)同侧半脑内参与肌肉激活的额叶和顶叶区域具有代偿作用。基于支持向量机算法的分类表明，与脑网络相比，准确率有所提高。这些结果说明了皮层肌肉系统在肌肉疲劳发展过程中的调节机制，并揭示了皮层肌肉网络在分析运动任务方面的巨大潜力。(2) 疲劳中动态力的增加导致皮质-肌肉网络活动从 β 波段转移到 γ 波段；(3)同侧半脑内参与肌肉激活的额叶和顶叶区域具有代偿作用。基于支持向量机算法的分类表明，与脑网络相比，准确率有所提高。这些结果说明了皮层肌肉系统在肌肉疲劳发展过程中的调节机制，并揭示了皮层肌肉网络在分析运动任务方面的巨大潜力。基于支持向量机算法的分类表明，与脑网络相比，准确率有所提高。这些结果说明了皮层肌肉系统在肌肉疲劳发展过程中的调节机制，并揭示了皮层肌肉网络在分析运动任务方面的巨大潜力。基于支持向量机算法的分类表明，与脑网络相比，准确率有所提高。这些结果说明了皮层肌肉系统在肌肉疲劳发展过程中的调节机制，并揭示了皮层肌肉网络在分析运动任务方面的巨大潜力。