INTEGRATION OF PHYSICAL ENDURANCE AND COGNITIVE RESILIENCE IN THE TRAINING OF PROFESSIONAL CYCLISTS - Horkusha Andrii (American Journals, 2026)
Prolonged endurance training in professional cycling increasingly requires the integration of physiological efficiency, neuromuscular stability, and cognitive resilience to meet race-specific demands. The purpose of this study was to evaluate the effectiveness of the author-developed Adaptive Rhythmic-Variable Endurance Training System (ARVETS), an original endurance training methodology integrating rhythmic workload variability, real-time neuromuscular correction, and cognitive–motor stimuli, in enhancing multidimensional endurance performance during long-duration cycling sessions. The study employed within-subject experimental design, continuous heart rate and power monitoring, Leg Balance Ratio (LBR) analysis, cadence variability assessment, and reaction time measurement to auditory stimuli under fatigue.Following the ARVETS intervention, cyclists demonstrated reduced cardiovascular drift, reflected in a lower heart rate–to–power ratio during the second and third training hours, prolonged time sustained at 70–88% FTP, and improved aerobic stability. Neuromuscular asymmetry was significantly reduced, with peak LBR during the final training hour decreasing from 6.3% to 3.2% (p < 0.05), followed by faster correction to 2.7%. Cognitive resilience improved as fatigue-related reaction time slowing was attenuated by 30 ms compared to baseline steady-state training (p < 0.05).The findings indicate that ARVETS promotes integrated physiological, neuromuscular, and cognitive adaptations rather than isolated performance gains. The scientific novelty lies in the unified endurance framework combining rhythmic variability, real-time neuromuscular correction, and cognitive load under fatigue. Future research should examine long-term competitive transfer effects and individualized ARVETS optimization strategies.
Keywords: Cardiovascular drift, neuromuscular symmetry, reaction time, cadence variability, endurance stability, cognitive load