TECH-4-kOA -TECHNOLOGY-based GAIT RETRAINING FOR KNEE OSTEOARTHRITIS: Computational modeling- and artificialintelligence-informed, real-life feedback on joint loading.

Osteoarthritis is the most common chronic joint disease, for which no proven prevention or cure exists that reverses or slows down the disease process. Aberrant joint loading accelerates OA progression. Gait-retraining, aiming to restore normal joint loading, therefore, has the potential to slow down OA progression. Previous gait retraining was based on indirect measures of knee joint loading, measured in a lab-based environment. Furthermore, no information on patientspecific muscle coordination and anatomy is considered. Musculoskeletal modelling allows researchers to accurately document the joint loading landscape, while overcoming previous shortcomings. Furthermore, predictive simulations can be used to determine an individually tailored gait retraining strategy that minimizes joint loading considering baseline gait pattern and joint anatomy. In this project, we combine computational modeling-based insights with a unique AI-augmented IMU-system to estimate patient-specific knee joint loading in real-world conditions and to provide feedback to correct the gait pattern. The consortium of researchers (KU Leuven, Université Laval en Université de Sherbrooke) therefore is in a unique position to develop technology-based gait-retraining as part of a lifestyle intervention program, in reach of the individual patient and his primary care physical therapist, and to evaluate their effect on OA symtoms.