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Injury Prevention and Rehabilitation Using Machine Learning for Athletes

Yadav, Mohit; Choudhury, Tanupriya; Huzooree, Geshwaree

Authors

Mohit Yadav

Tanupriya Choudhury



Contributors

Tanupriya Choudhury
Editor

Pradeep Kumar Arya
Editor

Ketan Kotecha
Editor

Ashutosh Sharma
Editor

Jung-Sup Um
Editor

Abstract

This chapter explores the role of machine learning (ML) in injury prevention and rehabilitation for athletes. It examines how ML models can predict injuries by analysing diverse data sources, such as biomechanics, wearables, and medical records, and highlights the potential for personalized, data-driven injury prevention strategies. The chapter also addresses how AI-driven rehabilitation programs can adapt in real-time to optimize recovery and reduce the risk of re-injury. Key challenges, such as data privacy, model complexity, and the need for explainable AI, are discussed, along with future trends like the integration of wearable technology, federated learning, and virtual reality in rehabilitation. These innovations promise to transform sports medicine by making injury prevention more accurate and rehabilitation more efficient, ultimately enhancing athlete performance and longevity.

Citation

Yadav, M., Choudhury, T., & Huzooree, G. (2025). Injury Prevention and Rehabilitation Using Machine Learning for Athletes. In T. Choudhury, P. Kumar Arya, K. Kotecha, A. Sharma, & J.-S. Um (Eds.), AI and Machine Learning Applications in Sports Analytics (129-156). IGI Global. https://doi.org/10.4018/979-8-3693-5385-1.ch007

Online Publication Date May 30, 2025
Publication Date May 30, 2025
Deposit Date Jun 2, 2025
Publisher IGI Global
Pages 129-156
Book Title AI and Machine Learning Applications in Sports Analytics
ISBN 9798369353851
DOI https://doi.org/10.4018/979-8-3693-5385-1.ch007
Public URL http://researchrepository.napier.ac.uk/Output/4521912