The team
Daniel Benoit (Principal Investigator, Medical Faculty), Andrea Dell’Isola (collaborator, Medical Faculty), Lorenzo Grassi (collaborator, Faculty of Engineering), Pär Halje (Collaborator, Faculty of Medicine).
The idea
Imagine being 16, full of energy, and loving sports—then a sudden knee injury changes everything. What seems like a short-term setback can quietly shape the rest of life. For many, an anterior cruciate ligament (ACL) tear during adolescence is the first step towards knee osteoarthritis (OA), a condition that often leads to pain, reduced mobility, and disability in later years.
ACL injuries have surged over time—from about 10 cases per 100,000 people in the 1950s to over 80 per 100,000 in Sweden today. Up to 87% of those affected may develop OA later in life, along with related health issues such as obesity, depression, and diabetes. These injuries often occur during puberty, a critical stage for physical and social development, making their impact even more profound.
This initiative aims to move beyond short-term recovery by predicting long-term risks and personalising care. A “digital twin” model will integrate multimodal data that will be analysed with the help of AI to guide tailored interventions.
Why it Matters
The approach seeks to reduce the societal and economic burden of long-term disability, improve quality of life, and support healthier ageing. By combining biomechanics, rehabilitation, AI, and health economics, the project offers a framework for early intervention and personalised care.