Neurophysiological and Muscular Adaptations During High-Intensity Cycling: A Pilot Study on Fatigue Dynamics

This pilot study explores the feasibility of carrying out a novel multimodal framework for analyzing physiological interactions in high-performance cycling. Using advanced sensors, biosignals such as electromyogram (EMG), electrocardiogram (ECG), electroencephalogram (EEG), muscle oxygen saturation (SmO₂), and oxygen consumption (VO₂) from one experienced cyclist during a progressive exercise test. Preliminary analysis revealed dynamic interactions between neural, muscular, and cardiovascular systems during fatigue transitions. Key findings include the dynamic adaptation of the brain, muscles, and cardiovascular systems during high-intensity cycling, with brain activity and muscle activation patterns changing to compensate for increasing fatigue. As exertion progresses, there is a decline in neural efficiency, muscle oxygenation, and autonomic regulation, with compensatory efforts in muscle activation and cardiovascular response to maintain performance until exhaustion. These insights highlight the utility of multimodal biosignal analysis approaches for understanding physiological complexities and contribute to real-time performance monitoring, injury prediction, and personalized training designs based on data. This study remarks the practicality of the experimental design and lays the groundwork for larger-scale investigations.