Table 1_Multimodal assessment of exercise-induced fatigue: integrating cardiopulmonary, neuromuscular, and biomechanical profiling in high-intensity running.docx

This study aimed to establish a multimodal framework integrating cardiopulmonary exercise testing (CPET), surface electromyography (sEMG), and plantar kinetic assessment to characterize neuromuscular and mechanical fatigue responses during high-intensity treadmill exercise. Twenty healthy collegiate male athletes performed an incremental CPET followed by a supramaximal verification phase. Gas exchange, heart rate, and perceived exertion were continuously recorded. Bilateral sEMG activity from the rectus femoris, biceps femoris, tibialis anterior, and gastrocnemius lateralis was analyzed for integrated EMG (iEMG), root mean square (RMS), and median frequency (MF). Pre- and post-exercise plantar kinetics were obtained using in-shoe pressure sensors to assess contact area, mean pressure, and vertical ground reaction force (VGRF). Plantar kinetics showed increased midfoot contact area (+12.3%, P = 0.01) and pressure (+10.8%, P = 0.03), along with elevated left-foot regional VGRF (P = 0.04), indicating side-specific post-exercise load redistribution. Although nominal correlations were observed between neuromuscular activation and post-exercise plantar loading, these associations did not remain statistically significant after false discovery rate (FDR) correction and should therefore be interpreted as exploratory. Rather than establishing a quantitative diagnostic threshold for fatigue, integrating cardiopulmonary, neuromuscular, and plantar kinetic measures contributes to a multidimensional characterization of fatigue-related adaptations beyond metabolic indicators alone. This multimodal framework illustrates how neural drive decline and mechanical load redistribution may co-occur under acute fatigue conditions, providing a structured approach for comprehensive fatigue profiling in athletic populations.

本研究旨在构建一套多模态研究框架，整合心肺运动试验（cardiopulmonary exercise testing, CPET）、表面肌电图（surface electromyography, sEMG）与足底动力学评估手段，以刻画高强度跑台运动过程中神经肌肉与机械疲劳的响应特征。20名健康高校男子运动员完成了递增负荷心肺运动试验，随后进行超最大负荷验证阶段。实验全程连续记录气体交换参数、心率与自觉用力程度。针对股直肌、股二头肌、胫骨前肌及腓肠肌外侧头的双侧表面肌电活动，分析其积分肌电（integrated EMG, iEMG）、均方根（root mean square, RMS）与中位频率（median frequency, MF）三项指标。分别于运动前后采用鞋内压力传感器采集足底动力学数据，评估接触面积、平均压力与垂直地面反作用力（vertical ground reaction force, VGRF）。结果显示，运动后中足接触面积增加12.3%（P = 0.01）、平均压力升高10.8%（P = 0.03），同时左脚局部垂直地面反作用力显著上升（P = 0.04），表明运动后足底负荷呈现侧特异性重分布现象。尽管观察到神经肌肉激活与运动后足底负荷间存在名义上的相关性，但经错误发现率（false discovery rate, FDR）校正后，此类关联不再具有统计学显著性，因此该结果仅可作为探索性发现解读。本研究并未建立疲劳的定量诊断阈值，而是通过整合心肺、神经肌肉与足底动力学指标，实现了超越单一代谢指标的疲劳相关适应性变化的多维度表征。这套多模态框架揭示了急性疲劳状态下神经驱动下降与机械负荷重分布可能共同发生的机制，为运动员群体的全面疲劳特征分析提供了结构化研究路径。