利用移动基座参考分析人体步态的增强型欧拉-拉格朗日公式

Sekar Anup Chander, Ashutosh Mukherjee, Vhatkar Dattatraya Shivling, Ashish Singla
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摘要

欧拉-拉格朗日公式以其在推导复杂系统动力学时的系统性和简化方法而著称。为了将现有公式应用于人体步态动力学,必须假设基础参考框架为惯性参考框架。通常,在人类行走的站立和摆动阶段,踝关节或髋关节被视为基础参考框架。由于这些关节在实际运动时是非惯性的,这种假设可能会导致下肢关节扭矩和力的计算不准确。因此,本文考虑并修改了最初为固定基座机器人操纵器开发的基于欧拉-拉格朗日的现有公式,以适应基座参照系相对于人体外惯性参照系的运动。我们使用三个标准的公开步态数据集研究、实施和验证了修改后公式的适用性,这些数据集涵盖了行走和跑步两个阶段。通过计算平均绝对误差值和直观的布兰-阿尔特曼图,将使用拟议动态模型获得的关节扭矩与参考扭矩进行比较。所获得的关节扭矩值和曲线图显示与已公布的扭矩值非常接近,从而验证了所提出的动态模型的准确性。该模型强大的公式实现能力使其成为该领域研究人员的宝贵资源,为步态分析和下肢假肢或外骨骼设计提供了可靠的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhanced Euler-Lagrange Formulation for Analyzing Human Gait with Moving Base Reference
Euler-Lagrange's formulation is known for its systematic and simplified approach in deriving dynamics of complex systems. In order to apply the existing formulation to human gait dynamics, the base reference frame must be assumed as an inertial reference frame. Conventionally, the ankle joint or the hip joint are regarded as base reference frames during the stance and swing phase of human walking. As these joints are non-inertial in nature during actual locomotion, this assumption could result in inaccurate calculation of lower-limb joint torques and forces. Therefore, in this paper, an existing Euler-Lagrange based formulation originally developed for fixed-base robotic manipulators is considered and modified to accommodate the movement of the base reference frame with respect to an inertial frame of reference defined outside the human body. The applicability of the modified formulation is studied, implemented, and validated using three standard and publicly available gait datasets covering the phases of walking and running. The joint torques obtained using the proposed dynamic model are compared with reference torques by calculating the mean absolute error values and visually through Bland-Altman plots. The obtained joint torque values and plots indicate a close agreement with published torques, thereby validating the accuracy of the proposed dynamic model. The robust formulation implementation makes it a valuable resource for researchers in this field, offering a reliable framework for gait analysis and the design of lower-limb prosthetics or exoskeletons.
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