Evaluating Joint Angle Data for Clinical Assessment Using Multidimensional Inverse Kinematics with Average Segment Morphometry.

Abstract

BackgroundQuantitative movement analysis is increasingly used to assess motor deficits, but joint angle calculations depend on assumptions about limb segment lengths. These lengths are often estimated from average anthropometric proportions rather than measured directly. The extent to which such assumptions influence joint angle accuracy and variability remains unclear. MethodsIn prior studies, we recorded reaching movements in nine healthy adults using active-marker motion capture system. In this study, we computed arm joint angles with a dynamic model scaled using either measured segment lengths (Individual method) or proportions based on body height (Average method). We compared segment proportions and the variability in joint angle trajectories arising from segment length assumptions (between-subject variability) with within-subject variability across repeated movements. ResultsSegment length proportions remained unchanged despite increases in population height. Joint angle trajectories derived from the two scaling methods were very similar. Segment length assumptions had only minor effects on joint angle amplitudes, primarily due to kinematic redundancy, and these effects were substantially smaller than the within-subject variability observed across repeated movements in most individuals. Importantly, while segment length estimates shifted absolute joint angle amplitudes, they did not alter the shape of angular trajectories. Conclusions/SignificanceMorphological variability in segment lengths contributes less to joint angle variability than the variability expressed by individuals across repeated movements. This indicates that movement variability is driven more by how the nervous system selects among redundant motor solutions than by body morphology. These findings suggest that clinical assessments of range of motion and movement quality are robust to the method of segment length estimation, supporting the reliability of motion capture-based assessments in both research and clinical settings. Author SummaryUnderstanding how people move is important for diagnosing and treating movement disfunction. Motion capture technology allows researchers and clinicians to measure how joints move, but these calculations depend on knowing the lengths of each arm segment. In practice, these lengths are often estimated from body height instead of being measured directly. We tested whether this assumption affects joint angle measurements. Using previously recorded reaching movements in healthy adults, we compared joint angles calculated from estimated versus measured arm segment lengths. We found that using estimated lengths had only a very small effect on joint angle trajectories, and these effects were much smaller than the natural variability that occurs when the same person repeats the same movement. This means that differences in body proportions do not significantly affect how arm movements are measured. Our findings show that motion capture is a reliable tool for assessing movement quality, even when exact body proportions are not measured, making it more practical for use in both research and clinical care.