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

PubDate:Oct 2023

Teams:  The University of Auckland;

Writers:Max Dang Vu,Gonzalo Daniel Maso Talou,Huidong Bai,Mark Billinghurst,Poul Michael FøNss Nielsen,Martyn Peter Nash,Thiranja Prasad Babarenda Gamage

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

Abstract

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 C1 of a cantilever beam using synthetic surface data. This workflow could be used for real-time navigational guidance during soft tissue treatment procedures.