WalkWell Gait reTrainer: Remote patient monitoring and gait retraining for knee osteoarthritis

Project summary

This project introduces the WalkWell Gait reTrainer, a wearable device for personalized gait retraining, improving daily life for knee osteoarthritis (OA) patients. The collaboration between Erasmus MC, TU Delft, and Moveshelf fosters interdisciplinary knowledge integration, promoting a convergence of expertise from diverse fields such as motion analysis, clinical care, and technological development, providing an innovative solution for knee OA care.

Knee OA is a leading cause of disability affecting millions worldwide. In the Netherlands, OA is expected to exceed 2.2 million patients by 2040. The total cost attributed to OA was almost €1.2 billion in 2019, of which 44% was attributed to the knee joint. The burden of OA is rising and is expected to continually increase with the ageing of the global population. This project addresses this challenge, aiming to revolutionize knee OA management.

OA is a complex, chronic disease predominantly caused by increased mechanical load on joint cartilage. Gait retraining has shown to modify mechanical load in knee OA patients, with real-time feedback to assist patients with optimizing gait patterns. Altering the foot progression angle, i.e., toe in or toe out, is relatively easy and reduces knee loading. Delivering real-time gait feedback with remote patient monitoring, potentially improves long-term outcomes for knee OA patients. Early and cost-effective interventions could reduce invasive medical interventions, hospitalizations, and long-term treatment costs.

Our objective is to design and evaluate a proof-of-concept of the WalkWell Gait reTrainer, an affordable, user-friendly continuous gait feedback system, complete with remote patient monitoring capabilities to support clinical care. We hypothesize that this system is usable in a community and home setting, enabling patients and clinicians to remotely monitor progress, to yield efficient and effective gait adaptations. The data collected in this study will be pivotal in planning future large-scale trials to assess the system’s efficacy.