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Artificial intelligence (AI) is revolutionizing sports physiology, offering deeper insights into athlete performance and well-being. By analyzing vast datasets from wearable sensors, physiological tests, and performance metrics, AI uncovers patterns that traditional methods often miss. This enables the development of personalized training programs, optimized recovery strategies, and proactive injury prevention. AI-driven biomechanics, heart rate variability analysis, and sleep monitoring provide real-time, objective assessments, allowing for immediate adjustments to training and recovery plans. Injury management is another critical area where AI excels. Advanced algorithms assess injury risks, assist in rehabilitation, and facilitate safe, efficient returns to competition. Talent identification also benefits, as AI evaluates physiological and biomechanical data to recognize promising athletes early. Additionally, emerging technologies like AI-powered virtual and augmented reality enhance skill acquisition and tactical training. Despite these advancements, ethical concerns such as data privacy, algorithmic bias, and accessibility must be addressed to ensure fair and responsible AI implementation. The key lies in balancing AI-driven insights with human expertise for comprehensive athlete development. As AI continues to evolve, interdisciplinary collaboration between data scientists, sports scientists, and coaches will be essential in fully harnessing its potential. With responsible integration, AI can drive innovation in sports science, ultimately improving athletic performance and overall well-being.
Keywords:
AI in sports, Athlete performance, Training optimization, Injury prevention, Physiological data
Cite Article:
"The Role of Artificial Intelligence in Sports Physiology: Advancing Performance and Supporting Athlete Wellness ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.a740-a744, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504093.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator