AI-controlled training method for performance hardening or injury recovery in sports
Attila Biró, Antonio Cuesta‐Vargas, László Szilágyi
Abstract
In the contemporary sports science domain, artificial intelligence (AI) has emerged as a pivotal tool, driving breakthroughs in athlete training and rehabilitation. Personalized training schedules, sculpted through AI algorithms, promise optimized performance and reduced injury likelihood. Wearable technologies, combined with AI-boosted functionalities, offer invaluable real-time physiological data, facilitating immediate training modifications or/and adjustments. The utilization of AI in biomechanical feedback has been groundbreaking, particularly in technique enhancement through meticulous gait analysis. The cognitive training tools are honing athletes’ decision-making and reflexes, attributes crucial in competitive scenarios. The psychological well-being of athletes is also catered to, with AI discerning early indicators of emotional strain. Furthermore, post-competition reviews have been enriched with AI-enabled video analytics, delivering nuanced insights for strategic refinements. The goal of this study was to provide an AI-assisted solution to identify problems in recovery exercises or to boost the athletes’ performance.