Complexity analysis of sEMG and IMU-based kinematics for muscular fatigue monitoring in dynamic sports settings

Muscular fatigue can significantly impair joint stability, alter proprioception, and increase injury risk in multidirectional sports such as football. While superficial electromyography (sEMG) is widely used for fatigue detection, signal non-stationarity during dynamic movements limits the reliability of traditional methods. This study assessed the potential of complexity-based sEMG features in capturing myoelectric manifestations of fatigue during a dynamic task incorporating sport-related movement patterns, while examining variability in lower-limb joint kinematics. Forty-five football players were monitored using a synchronised wearable system comprising sEMG and Inertial Measurement Units (IMUs) during a running activity with unpredictable directional changes. Spectral sEMG features (Median Frequency and Instantaneous Median Frequency) were compared with complexity-based indices (Sample Entropy, SE; Permutation Entropy) across six muscles. Results suggest that SE may offer enhanced robustness against motion-related non-stationarity, exhibiting a progressive decrease across muscles. Specifically, the most consistent fatigue-related adaptations were observed in the soleus and the vastus medialis (p < 0.001). Concurrently, alterations in joint motion variability patterns were observed in the hip, knee, and ankle during the running cycle, which may reflect fatigue-induced adaptations. These findings suggest that SE is a promising indicator for monitoring neuromuscular adjustments in dynamic conditions. Furthermore, exploring the co-occurrence between complexity-based sEMG trends and IMU-derived kinematics offers a valuable approach for contextualising adaptations in neuromuscular control during a challenging dynamic task. Algorithmic estimates suggest the theoretical feasibility of near-real-time computation, though full system validation in real-world sports environments remains a prerequisite for formally recommending coaching applications or injury-prevention strategies.