KneeTwin

KneeTwin aims to build a “digital twin” of each patient undergoing knee replacement, helping clinicians predict how recovery is likely to unfold before surgery and identify risks early.

By collecting real‑world movement data from large groups of patients and analysing it to extract digital biomarkers, the project will create personalised recovery profiles. This supports better-informed decisions before the operation, earlier detection of problems during rehabilitation, and more tailored follow‑up care. While the initial focus is knee replacement, the approach can be applied to other conditions where mobility is central.

Main researcher:

Shima Gholinezhad, Pernille Damborg Clasen

Co-researchers from the group:

Ole Rahbek, Søren Kold, John Rasmussen

External Researcher:

Andreas Kappel, Per Henrik Randsborg