Sit-to-stand (STS) motion is one of the most important tasks in daily life and is one of the key determinants of functional independence, especially for the senior people. The STS motion has been extensively studied in the literature, mostly through experiments. Compared to numerous experimental studies, there are limited simulations with mostly assuming bilateral symmetry for STS tasks. However, it is not true even for healthy individuals to perform STS tasks with a perfect bilateral symmetry. In this study, predictive dynamics is utilized for STS prediction. The problem can be constructed as a nonlinear optimization formulation. The digital human model has 21 degrees of freedom (DOFs) for the unassisted STS tasks. The quartic B-spline interpolation is implemented for representing joint angle profiles. The recursive Lagrangian dynamics approach and the Denavit–Hartenberg method are implemented for the equations of motion. This study is to develop a generic three-dimensional unassisted STS motion prediction method for healthy young and elderly individuals. Results show that trunk joint angle peak values are similar between the two virtual-groups in the sagittal, frontal, and transverse planes. Lower-limbs’ joint angle and velocity profiles and their peak values between the right and left side for both virtual groups are also similar. The normalized peak joint torques are slight differences in each active DOF between the two virtual groups and the peak values are similar. The proposed method has been indirectly validated through the literature experimental results. The developed method has various potential applications in the design of exoskeleton, microelectromechanical system for fall detection, and assistive devices in rehabilitation.

中文翻译：

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虚拟健康的年轻人和老年人的三维无辅助坐着站立预测

坐姿（STS）运动是日常生活中最重要的任务之一，并且是功能独立性的关键决定因素之一，特别是对于老年人而言。STS运动已在文献中进行了广泛的研究，主要是通过实验。与大量的实验研究相比，在有限的模拟中，大多数假设STS任务的双边对称性。但是，即使是健康个体，也无法以完美的双边对称性执行STS任务。在这项研究中，预测动力学用于STS预测。该问题可以构造为非线性优化公式。数字人体模型具有21个用于辅助STS任务的自由度（DOF）。四次B样条插值用于表示关节角度轮廓。对于运动方程，采用了拉格朗日递归动力学方法和Denavit-Hartenberg方法。本研究旨在为健康的年轻人和老年人开发一种通用的三维无辅助STS运动预测方法。结果表明，在矢状，额状和横状面的两个虚拟组之间，躯干关节角度峰值相似。两个虚拟组的下肢关节角度和速度曲线及其在右侧和左侧之间的峰值也相似。归一化的峰值关节扭矩在两个虚拟组之间的每个活动自由度中都略有不同，并且峰值相似。通过文献实验结果间接验证了该方法的有效性。