AI RESEARCH

SSPINNpose: A Self-Supervised PINN for Inertial Pose and Dynamics Estimation

arXiv CS.LG

ArXi:2506.11786v2 Announce Type: replace Accurate real-time estimation of human movement dynamics, including internal joint moments and muscle forces, is essential for applications in clinical diagnostics and sports performance monitoring. Inertial measurement units (IMUs) provide a minimally intrusive solution for capturing motion data, particularly when used in sparse sensor configurations. However, current real-time methods rely on supervised learning, where a ground truth dataset needs to be measured with laboratory measurement systems, such as optical motion capture.