DataDriven Sports Medicine: Deep Learning Insight s with Blockchain Trust

This essential guide bridges cutting-edge AI and blockchain with real-world sports medicine, equipping you with actionable techniques to pioneer the future of athletic performance and modern care ecosystems.

This book presents a comprehensive exploration of the intersection between artificial intelligence, blockchain technology, and sports medicine. Offering a structured approach, the book progresses from foundational principles to advanced applications and future directions. The early chapters introduce the fundamentals of data-driven sports medicine, deep learning architectures, and transformers, and their applications in biomechanics and performance analysis. Building on these foundations, it delves into applied deep learning techniques in sports medicine through real-world applications, including athlete performance monitoring via wearable sensors, injury prediction and prevention using musculoskeletal modeling, computer vision for gait and pose estimation, and the design of personalized training and rehabilitation plans through adaptive recommendation systems. The book concludes with critical discussions of deployment challenges, regulatory and ethical concerns, global case studies across sports disciplines, and visionary future directions such as AR/VR, digital twins, and autonomous sports care ecosystems. This essential guide serves as a solid technical grounding and a forward-looking perspective on how AI and blockchain are reshaping the field of sports medicine.

Abhishek Kumar, PhD, is an Assistant Director and Associate Professor in the Computer Science and Engineering Department at Chandigarh University, Punjab, India. He has authored seven books, edited 51 books, and published more than 170 publications in reputed, peer-reviewed national and international journals, books, and conferences. His research areas include artificial intelligence, renewable energy, image processing, computer vision, data mining, and machine learning.

Pramod Singh Rathore, PhD, is an Assistant Professor in the Department of Computer and Communication Engineering at Manipal University Jaipur. With more than 12 years of academic teaching experience, he has published more than 85 papers in reputable, peer-reviewed national and international journals, books, and conferences. His research interests include NS2, computer networks, and mining.

Inam Ul Haq is an Assistant Professor in the School of Engineering and Technology at CGC University, Mohali, India. He has published 51 research articles and has actively participated in academic and research activities. His research interests include artificial intelligence, machine learning, deep learning, large language models, renewable energy, wind energy, and bioinspired algorithms.

Pooja Dixit is an Assistant Professor in the Department of Computer Science at Shri Ratanlal Kanwarlal Patni Girls’ College, Kishangarh, India. With more than ten years of academic teaching and two years of research experience, she has published more than 30 research papers in reputed journals, books, and conferences. Her research interests include artificial intelligence, machine learning, and data mining.

Sachin Ahuja, PhD, is a Professor and Executive Director of UIE at Chandigarh University. He has led multiple funded research projects in artificial intelligence, machine learning, and data mining and has contributed to numerous academic books. He has also served as a guest editor for special issues in reputed international journals.