Comparison of lower limb kinematics and kinetics estimation of basketball players during jumping with markerless and marker-based motion capture systems

Basketball requires high lower limb performance. Assessing jump biomechanics is vital for enhancing performance and injury prevention. Marker-based (MB) systems are common but limited. In recent years, Markerless (ML) motion capture systems have gradually become emerging tools in sports biomechanics research due to their characteristic of not requiring physical marker points. However, their specific application and verification in basketball events are still relatively limited. <i>Purpose</i>: In this study, lower limb kinematics and kinetics estimated by MB and ML motion capture systems during jumps were compared. <i>Methods</i>: Twelve subjects performed the standing vertical jump (SVJ), standing long jump (SLJ) and running vertical jump (RVJ) tests. Data was collected using 10 infrared cameras, 6 high-resolution cameras and two force platforms via Vicon Nexus software. Markerless motion capture calculated sagittal plane angles, torque and power of the Hip, Knee and Ankle joints via Theia3D software, with these parameters also collected by the marker-based Vicon system. Both systems' '64ata were then processed in Visual3D. We analyzed the correlation coefficient (<i>r</i>), root mean square difference (RMSD), and maximum/minimum errors, as well as using statistical parametric mapping (SPM) to compare temporal patterns between groups and determine specific moments where significant differences occurred. <i>Results</i>: SLJ capture was slightly inferior in both systems. SPM analysis of the sagittal plane showed significant differences only at the hip joint. Joint angle RMSD was < 8.2°, torque RMSD < 0.41 N·M/kg, and power RMSD < 1.76 W/kg. <i>Conclusions</i>: The ML system accurately captures knee and ankle joints in the sagittal plane but shows significant differences in hip measurement and certain movements, requiring further validation.