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Repeated-measures study reveals significant joint measurement discrepancies between markerless motion capture systems in healthy adults, highlighting the need for single-device tracking.
Background: Markerless motion capture systems are increasingly used in clinical and educational settings to assess functional movement. However, differences in system design and data processing may influence measurement outputs, raising questions about the systematic differences in these technologies. Methods: A within-subject, repeated-measures design was used to compare range of motion (ROM) measurements obtained from two markerless motion capture systems during a sit-to-stand task. Fifty healthy adults (18–50 years) performed the task under three surface conditions (firm, compliant, and commode) while both systems recorded movement simultaneously. Joint ROM at the trunk, hips, knees, and ankles was analyzed using linear mixed-effects modeling to examine device, surface, and interaction effects. ROM was standardized to account for differences in absolute ROM magnitude and variability across biomechanically distinct joint measures. Results: A linear mixed-effects model showed significant main effects of both Device and Surface (all p’s < 0.001). There were also significant interactions between Device × Surface (p = 0.032), Device × Joint (p < 0.001), and Surface × Joint (p < 0.001), indicating that differences between devices and surfaces varied across biomechanical measures. The device-related discrepancies in standardized ROM (zROM) were greatest for hip adduction and trunk forward lean, whereas smaller between system differences were observed for ankle dorsiflexion and knee flexion. The firm surface demonstrated relatively larger zROM measurements for ankle dorsiflexion, knee flexion, and hip flexion compared to the compliant and commode surfaces. Conclusions: Markerless motion capture systems produced systematically different measurements during a functional task, and these differences were influenced by movement type and task conditions. The findings suggest that kinematic data derived from different markerless motion capture systems should be interpreted cautiously when comparing movement performance. Consistent use of a single system may be important for clinical tracking, and educational programs should emphasize critical interpretation of technology-derived movement data.
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Voltmer et al. (2026) studied this question.
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