| Application of Artificial Intelligence in Running Biomechanics: a Narrative review |
| Paper ID : 1236-SPORTCONGRESS (R1) |
| Authors |
|
Ali Rasouli Pour Khameneh *1, Zahra Mazhar Sarmadi2, Elham Shirzad3 1Department of Sport Biomechanics, Faculty of Sport Science and Health, University of Tehran, Tehran, Iran 2Department of Sport injuries & Biomechanics, Faculty of Sport science, University of Kharazmi 3Department of Sport injuries & Biomechanics, Faculty of Sport Sciences & Health, University of Tehran |
| Abstract |
| Abstract Introduction: Artificial Intelligence (AI) has become a transformative tool in running biomechanics, enabling real-world assessments, performance optimization, and injury prevention. Traditional laboratory methods, such as marker-based motion capture and force plates, provide precise measurements but are limited in accessibility and scalability. Methods: This narrative review synthesized 31 studies focusing on markerless motion capture, wearable-sensor-based kinetic prediction, injury-risk modeling, and AI-mediated feedback systems. Key advances, challenges, and future directions are highlighted. Results: Running biomechanics is essential for understanding movement patterns, performance outcomes, and injury mechanisms. Conventional laboratory methods are accurate but impractical for field-based applications. AI, including machine learning and deep learning, extends biomechanical analysis to real-world conditions by leveraging video-based pose estimation and wearable sensors [1–4]. Conclusion: This review examines AI applications in running biomechanics with a focus on performance enhancement and injury prevention. AI has advanced running biomechanics, enabling field-based analysis and real-time feedback. Challenges include limited dataset diversity, model generalizability, and real-time deployment. Future research should prioritize large, heterogeneous datasets, transparent validation, and long-term trials assessing whether AI-guided interventions improve performance and reduce injury risk. Keywords: Biomechanics- Kinetic- Kinematic- Running- AI |
| Keywords |
| Biomechanics- Kinetic- Kinematic- Running- AI |
| Status: Abstract Accepted (Oral Presentation) |
