Injury prediction in sports using artificial intelligence (I-PredictAI)


Context :

Sports injury prevention is an important aspect of athlete health, given the physical, psychological and social consequences injuries may have, in both short- and long-term perspectives. The preventive measures currently proposed to athletes are not sufficiently implemented in practice, and do not seem highly effective in real-world settings. A more individualized approach using artificial intelligence analysis tools and which considers the multifactorial nature of the injury, the athlete’s individual deficiencies/risk factors and the athlete’s environment, and their possible modifications over time could be more efficient.

Goals :

The objectives of this PhD thesis are 1) to develop algorithms that estimate the risk of sports injury occurrence based on a multi factorial approach, and 2) to assess the effectiveness of using these risk-estimation algorithms to reduce the occurrence of sports injuries by individually guiding athletes in their athletic practice.