A Variable-Length Upper-Body Link Model for Improved 2D Joint Position Estimation in Standing Movements

Abstract The human body has been extensively modeled for motion analysis and state estimation. In nursing care and workplaces, where large-scale measurement systems are impractical, a simpler system to measure the human body is required. Therefore, owing to their simplicity, two-dimensional human-link models in the sagittal plane are commonly used. If all link lengths are fixed, the model fails to compute certain postures owing to discrepancies with the actual human body. Hence, models have been proposed in which only the thigh or upper arm link length is variable, using changes in the apparent link length with human posture. The model can absorb errors by introducing variability in link lengths. The variable-length upper-arm model, which considers shoulder degrees of freedom, introduces relatively small errors but exhibits significant inaccuracies depending on posture. In this study, we analyzed human standing motion to propose a variable-length upper-body link model that maintains simplicity while reducing joint position errors across different postures. Because the upper body can flex, its apparent link length changes considerably, which helps reduce joint position errors. To validate the proposed model, we targeted users of standing support robots and compared the joint position errors obtained from both the proposed and existing models against actual positions. The standing up movements of eight young healthy individuals were measured, and the errors were compared using VisionPose® s the ground truth. The results of the t-test indicate that the model estimates joint positions with greater accuracy while being as simple as the existing models.