🤖 AI Summary
This study addresses the clinical need for a convenient and low-cost method to quantify joint angles. The authors propose a novel approach that directly maps segment rotation matrices—output by arbitrary parametric human body models such as GEM-X or SAM 3D Body—to clinically relevant joint angles, without requiring inverse kinematics, musculoskeletal modeling, subject-specific calibration, height measurements, camera parameters, or individualized modeling. Relying solely on a compact calibration table, the method is computationally efficient, enables real-time processing of monocular video, and demonstrates cross-model generalizability. Evaluated on the OpenCap LabValidation dataset, it achieves a mean absolute error of 4.50 degrees, matching the performance of OpenCap Monocular.
📝 Abstract
Quantitative joint angles are rarely available in routine care because the tools are slow, costly, or confined to a laboratory. We show that clinical joint angles can be read directly from the per-segment rotation matrices a parametric body model already produces, with no inverse-kinematics or musculoskeletal-model fitting step. On the OpenCap LabValidation cohort, using the GEM-X body-model estimator on single-smartphone video, our pooled mean absolute error is 4.50 degrees over the fifteen joint angles that match the OpenCap Monocular reference set, the same accuracy range as OpenCap Monocular's 4.8 degrees on the same cohort and reference standard, from a much simpler pipeline. The step that connects a body model to clinical angles is a small calibration table rather than an optimisation, so the same procedure transfers unchanged to other body models: repeating it on SAM 3D Body, changing only the table, gives 4.66 degrees, statistically indistinguishable from GEM-X, and runs in real time from a live single-camera stream. The method needs no per-recording inputs beyond the video itself: no participant height, no camera-intrinsics database, no per-subject model scaling. This broadens where movement analysis is practical, from in-clinic and at-home recording to telerehabilitation and large-scale decentralised studies.