The integration of artificial intelligence (AI) and multimodal data analytics is profoundly reshaping the domains of sports and human health. Traditional practices, focused on biomechanics and training optimization, are now becoming much more sophisticated, aimed at not just maximizing athletic performance but ensuring comprehensive physical and mental well-being. Technological advancements in AI, machine learning, and deep learning have unlocked opportunities for personalized and holistic health management strategies, tailored to the physiological and psychological needs of individual athletes.

Despite the recognized importance of physical factors such as injury prevention, performance enhancement, and rehabilitation, the contribution of psychological well-being—addressing stress, anxiety, and depression—remains vital yet underexplored. The fusion of multifaceted datasets, capturing biomechanics, physical behaviour, physiological metrics, and psychological states, presents an exciting research frontier ripe for exploration.

This Research Topic addresses the integrative use of AI and multimodal analytics to advance sports performance, injury prediction and rehabilitation, psychological health monitoring, and personalized health strategies. Of particular importance is the enhanced role of biomechanics and physical behaviour analysis—ranging from movement efficiency, posture control, and motor coordination, to muscular and skeletal load management—which, when coupled with AI, offers deeper insights into performance optimization and injury prevention.

Future research must bridge the gap between AI innovations and applied sports and health sciences, emphasizing a transdisciplinary approach that includes biomechanics, physical behaviour analysis, psychology, sports medicine, and neuroscience. Our primary aim is to foster research that provides practical insights and implementations for athletes, coaches, clinicians, and health professionals by using wearable technologies, virtual reality (VR), and augmented reality (AR).

To gather further insights into this wide-ranging and innovative field, we welcome articles addressing, but not limited to, the following themes:

- Integrated AI tools for injury prediction and prevention, including advanced machine learning models and real-time biomechanical analysis

- AI-based analysis of physical behaviour patterns, such as movement dynamics, gait analysis, and motor function adaptation

- Multimodal sensor data utilization for personal rehabilitation and training, with an emphasis on wearable sensors and smart textiles

- AI-enhanced athletic performance optimization using novel architectures and interactive training environments like VR and AR

- Methods for AI-driven psychological and emotional health management, detecting early signs of mental health issues in athletes

- Real-world application and validation of AI innovations in sports settings, focusing on interdisciplinary integration

- Theoretical and methodological innovation in AI tailored to sports-related data, including advanced deep learning methods

Ultimately, this Research Topic aims to significantly enrich our understanding of how AI-driven technologies and multimodal data approaches can comprehensively transform and enhance athletic performance and human health management strategies, emphasizing both physical achievements and mental resilience.

Are you interested in contributing a manuscript to this Research Topic?

Transforming Sports and Health: AI-Driven Performance Optimization, Biomechanics, and Psychological Well-being