Innovative tools to improve knee health and predict an athlete’s risk of anterior cruciate ligament (ACL) injury

Anterior cruciate ligament (ACL) injuries are one of the most frequent injuries among athletes. Currently, the only way to predict an individual’s risk of incurring an ACL injury is through prohibitively expensive motion analysis laboratories. There is a critical need to develop novel tools that improve knee-health and are well-received by the athletic community.
This proposal will develop (1) a Kinect-ACL Injury Prediction System (K-AIPS-pro) for sports-medicine and orthopaedic clinics to: (i) score the risk of ACL and secondary injury; (ii) an athlete’s ability to return to play; and (iii) identify biomechanical features to promote knee-health using a personalized exercise plan, and (2) a Smartphone-Knee Improvement Performance System (SKIPS) for athletes. Through the integration of exercise videos and knee health tutorials, SKIPS represents a tool enabling athletes to take preventative measures to reduce their risk of ACL injury.

Faculty Supervisor:

Paul Martineau

Student:

Partner:

Emovi Inc

Discipline:

Life Sciences

Sector:

Manufacturing

University:

Research Institute of the McGill University Health Centre

Program: