Estimating mechanical properties of soft objects using surface measurements from AR headsets

Physics-driven predictions of soft tissue mechanics are vital for various medical interventions. Insights on the mechanical properties of soft tissues are essential for obtaining personalised predictions from these models. This study aims to provide a workflow to identify the material parameters of soft homogeneous materials under gravity loading using 3D surface geometrical measurements acquired from a wearable augmented reality (AR) headset's depth camera. Preliminary results show that the parameter estimation procedure can successfully recover the ground truth material parameter C-1 of a cantilever beam using synthetic surface data. This workflow could be used for real-time navigational guidance during soft tissue treatment procedures.