Grant: Project Grant

Anterior Cruciate Ligament (ACL) injuries are a common and debilitating injury in children who participate in sport. These injuries are known to increase the risk of osteoarthritis and future re-injury and in severe cases, require surgical reconstruction and months of rehabilitation before returning to daily activities and sport. To mitigate the chance of future re-injury and ensure a safe return to mobility for both school and sport, children are usually assessed over a range of common movements by a doctor after recovery. But, because each child, each injury, and each recovery are different, performance on standardized movement assessments can vary considerably. To improve the process of return to sport decisions, we propose to quantify and characterize the differences in movement ability between healthy children and those at 9 months following ACL reconstruction surgery. This will inform us on the expected variations within standardized assessments. Because return to sport assessments occur only once at 9 months post-surgery, we also propose to evaluate state-of-the-art deep learning methods that will ultimately help track recovery in the home using camera videos of movement assessments. Such technologies have been utilized in adults to track movement recovery and rehabilitation but have not been effectively evaluated or translated to children, despite the high incidence of injuries and their debilitating consequences. These tools will provide a more complete picture of the recovery process, and in the future will allow clinicians and physiotherapists to personalize treatment during the recovery period. Overall, this work seeks to better understand how to make return to sport decisions following an ACL injury to provide children the best chance of a full recovery without re-injury and further complications.