Does the Fuzzy Control-based Training Optimization Framework (FC-TOF) improve training results and reduce injury rates in athletes compared to traditional techniques?
The Fuzzy Control-based Training Optimization Framework provides a personalized, data-informed approach to improve athletic performance and reduce training-related hazards.
Optimizing sports training intensity is essential for enhancing athletic performance while minimizing the risks of overtraining and injury. Traditional methods often lack the adaptability needed to accommodate an athlete’s dynamic and physiological responses. To address this, the study introduces the Fuzzy Control-based Training Optimization Framework (FC-TOF), an intelligent and adaptive approach to managing training intensity. The FC-TOF integrates fuzzy control techniques with real time physiological data, such as heart rate variability, perceived exertion, and training volume. These inputs are processed through a fuzzy logic system to provide personalized, dynamic training intensity adjustments based on individual performance goals and physical conditions. The FC-TOF has been validated using historical athlete data and tested on participants from various sports disciplines. The implementation of FC-TOF exhibited significant enhancements in training results. Athletes exhibited increased endurance, superior peak performance measures, reduced injury rates, and more effective recovery management than traditional techniques. The technology promoted improved adherence to training schedules by offering personalized, data-informed recommendations. This study highlights the efficacy of FC-TOF as a useful tool for improving sports training intensity. The study provides a dependable basis for personalized training methodologies, improving athletic performance while mitigating training-related hazards.
Yan et al. (Sun,) studied this question.