Exploring the Integration and Implications of Artificial Intelligence Chatbots in the Realm of Sports Science Research, Training, and Rehabilitation

Authors

  • Touhami Hamdaoui Laboratory of Biological and Psychological Responses to Physical and Sports Activity, University of Mohammed Cherif Messaadia, Souq Ahras, Algeria Author https://orcid.org/0009-0009-2098-7889
  • Noureddine Ghennam Laboratory of Biological and Psychological Responses to Physical and Sports Activity, Université Larbi Ben Mhidi - Oum El Bouaghi, Oum El Bouaghi, Algeria Author https://orcid.org/0009-0008-1343-4154
  • Rami Bouchouareb Laboratory of Biological and Psychological Responses to Physical and Sports Activity, Université Larbi Ben Mhidi - Oum El Bouaghi, Oum El Bouaghi, Algeria Author https://orcid.org/0009-0008-2851-5643
  • Hatem Ghouili High Institute of Sport and Physical Education of Kef, University of Jendouba, El Kef, Tunisia Author https://orcid.org/0000-0002-9558-5448

Keywords:

Artificial Intelligence, Athletic Monitoring, Chatbots, Injury Prevention, Performance Optimization, Rehabilitation, Sports Science, Talent Identification

Abstract

Background: The field of sports science has been fundamentally transformed by the integration of artificial intelligence (AI) technologies. AI has enabled advances in areas such as performance optimization, training personalization, injury risk assessment and prevention, talent recognition, rehabilitation, athlete monitoring, and wellness optimization.

Objective: This review aims to explore the diverse impact of AI in sports science, highlighting advances in AI techniques, the challenges and limitations of integrating AI tools, and the emerging role of AI chatbots in shaping the future of sports research and applications.

Methods: The review examines the existing literature on the application of machine learning, deep learning and other AI techniques in various aspects of sports science research and practice. It provides an overview of how these technologies have been used to improve personalized training programs, video analysis, injury risk prediction, talent identification, and rehabilitation.

Results: The article describes how AI-powered tools and techniques have revolutionized sports science, enabling personalized, data-driven and efficient approaches to performance optimization. Sophisticated machine learning algorithms such as artificial neural networks, decision trees and support vector machines have been used to develop predictive models for injury risk assessment and prevention, leading to improvements in athletes' wellbeing and long-term performance. AI-driven talent identification and selection processes have also shown promise in recognizing exceptional athletes with greater accuracy. In addition, the integration of AI into athlete monitoring and rehabilitation has led to greater personalization, better decision making and faster return to play.

Conclusion: The integration of AI and machine learning techniques into sports science has the potential to transform the field and lead to improved athlete performance, reduced risk of injury, improved well-being, and more personalized and effective interventions. The emergence of AI chatbots expands the applications of these technologies in sports science and offers new opportunities to streamline research processes, provide personalized advice to athletes and support sports medicine and rehabilitation

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Published

2024-09-29

How to Cite

Hamdaoui, T., Ghennam, N., Bouchouareb, R. ., & Ghouili, H. . (2024). Exploring the Integration and Implications of Artificial Intelligence Chatbots in the Realm of Sports Science Research, Training, and Rehabilitation. Tunisian Journal of Sports Science and Medicine, 2(3), 6-16. https://tunjsportscimed.com/index.php/tjssm/article/view/25

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