New Paper published in "Scientific Reports"

Bernhard Färber¹, Brian Horsak^2,3 & Florian Kurt Paternoster¹

¹ TUM School of Medicine and Health, Associate Professorship of Biomechanics in sport, Technical University of Munich, Am Olympiacampus 11, 80809 Germany, Munich, Germany. 
² Center for Digital Health and Social Innovation, St. Pölten University of Applied Sciences, Campus-Platz 1, St. Pölten 3100, Austria. 
³ Institute of Health Sciences, St. Pölten University of Applied Sciences, Campus- Platz 1, St. Pölten 3100, Austria.

Abstract
3D motion analysis (3DMA) can help identify patients at increased risk of ACL re-injury, but traditionalmarker-based systems have limited clinical accessibility. OpenCap, a novel, low-cost, markerlesssystem, aims to enhance accessibility to 3DMA. This study evaluated the concurrent validity of amodified OpenCap version using a 2-DOF knee model for kinematics, while kinetics and groundreaction forces were derived using the native 1-DOF model, compared to a marker-based system.Twenty-four healthy participants performed 240 drop jumps, with data simultaneously captured byboth systems. Root mean square error (RMSE), mean absolute error (MAE), maximum error, Pearsoncorrelation, Bland-Altman plots, and statistical parametric mapping (SPM) were used to analyzeinter-system differences. RMSE exceeded 6° for frontal-plane knee kinematics with strong waveformcorrelations (r > 0.90). Transverse-plane hip moments showed normalized MAE < 1% with weak tostrong negative correlations. Sagittal-plane knee moments had normalized MAE of 5.6% and strongcorrelations (r > 0.90). Vertical GRFs showed normalized MAE > 6% and strong correlations (r > 0.90).SPM identified significant differences across most ground contact phases, and Bland-Altman analysesshowed wide agreement limits for knee moment asymmetry at initial contact. OpenCap currentlycannot be recommended for ACL re-injury risk assessment but demonstrated potential for increasing3DMA accessibility.

Keywords 
Anterior cruciate ligament injuries, Markerless motion capture, 3D kinematic analysis, Biomechanical validation, Re-injury prevention

Full Text Link (Open Access)