Enhancing Individual Sports Training through Artificial Intelligence: A Comprehensive Review

Abstract

The integration of artificial intelligence (AI) in sports training has emerged as a transformative approach to enhancing individual performance, optimizing training strategies, and providing personalized insights for athletes and coaches. This article presents a comprehensive review of the applications, algorithms, challenges, and future directions of AI in individual sports training. We explore the utilization of AI algorithms and techniques, including machine learning, deep learning, and computer vision, in sports apps to personalize training programs, analyze performance, provide feedback, assess injury risks, and optimize training methodologies. The article examines the scientific foundations of AI-enhanced sports training, discussing the personalization and customization of individual training, performance analysis and feedback using AI-powered tools, injury prevention and risk assessment through AI models, user experience and interface design considerations, ethical implications and data privacy, case studies and empirical evidence, challenges, and recommendations for further research. We highlight the potential of AI in transforming the way athletes train, providing tailored interventions, and optimizing performance outcomes. The article concludes by identifying areas for future research, including advanced data analytics, explainable AI models, ethical considerations, collaboration, longitudinal studies, optimization of training programs, human-AI interaction, and generalization to diverse populations. By addressing these research avenues, the field of AI-enhanced sports training can continue to evolve, supporting athletes and coaches in achieving their goals and unlocking new dimensions of performance optimization.