Racket sports, including tennis, badminton, table-tennis, baseball, and squash, present a complex interplay between the athlete, the equipment, and the environment. The fast-paced, repetitive, and asymmetrical nature of strokes, coupled with high-impact acceleration and multidirectional footwork, imposes complex biomechanical loads that are closely linked to both acute and overuse injuries in the lower limbs, lumbo-pelvic region, and dominant upper extremity. In recent years, technological advancements have facilitated the use of wearable sensors, marker-less motion-capture systems, smart rackets, and pressure-mapping technologies, which can gather multi-modal data during training or competition. However, while AI and machine learning have matured to interpret large data streams into insights for injury-risk stratification and real-time technique modification, the racket sports community lacks integrated frameworks that connect biomechanical research, injury prevention, and AI-driven intervention coherently.

The goal of this Research Topic is to deepen our understanding of mechanical mechanisms in racket sports, promote injury prevention, optimize performance, and advance footwear development through biomechanical experiments, computer simulations, and AI technology. The aim is to uncover deeper insights and validate effective sports practices using computational methodologies such as musculoskeletal modeling, finite element analysis, machine learning, and multi-scale modeling. Our objective is to establish a closer connection between traditional biomechanical theory and modern technological advancements and to translate research findings into practical sports scenarios.

This Research Topic focuses on advancing three core areas: (1) the high-fidelity measurement of biomechanical loading specific to racket sports, (2) the epidemiological and mechanistic understanding of injury pathways, and (3) the deployment of AI-enabled tools for prediction, prevention, and on-court feedback. To gather further insights in these areas, we welcome articles addressing, but not limited to, the following themes:

o Musculoskeletal modeling and simulation of racket sports

o Biomechanical optimization of sports skill and performance

o Personalized biomechanical models for injury prevention and rehabilitation

o Applications of finite element analysis in injury prevention and sports performance

o Machine learning and artificial intelligence in biomechanical data analysis

o Footwear, equipment, and wearable design in racket sports

o Motion analysis, joint loading, stiffness, and muscle activities in racket sports

o Movement behavior studies across different racket sports

o Real-time biomechanical feedback systems for players

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Insights into biomechanics, injury prevention, and AI to promote racket sports