优化合并运动学和动力学信息,确定整个身体的质心位置

Charlotte Le Mouel
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引用次数: 0

摘要

身体质心(CoM)的轨迹对于评估平衡至关重要。质心位置可通过运动学或动力学方法计算得出。每种方法都有其局限性,而且很难评估其准确性,因为没有可与 CoM 轨迹进行比较的基本事实。在本文中,我们使用以下事实作为基本事实:在跑步的飞行阶段,CoM 的加速度等于重力。我们评估了不同复杂程度的运动学模型的准确性,发现误差范围从重力的 14% 到 38%。我们提出了一种优化组合运动学和力板信息的新方法。使用这种方法后,所有运动学模型的误差都降至 3 % 左右。计算这种优化组合的代码有 Python 和 Matlab 两种版本:https://github.com/charlotte-lemouel/center_of_mass。文档可在以下网址获取: https://center-of-mass.readthedocs.io
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal merging of kinematic and kinetic information to determine the position of the whole body Center of Mass
The trajectory of the body center of mass (CoM) is critical for evaluating balance. The position of the CoM can be calculated using either kinematic or kinetic methods. Each of these methods has its limitations, and it is difficult to evaluate their accuracy as there is no ground truth to which the CoM trajectory can be compared. In this paper, we use as ground truth the fact that, during the flight phase of running, the acceleration of the CoM is equal to gravity. We evaluate the accuracy of kinematic models of different complexity and find that the error ranges from 14 % to 38 % of gravity. We propose a novel method for optimally combining kinematic and force plate information. When using this proposed method, the error drops to around 3 % for all kinematic models. The code for calculating this optimal combination is available in both Python and Matlab at: https://github.com/charlotte-lemouel/center_of_mass. The documentation is available at: https://center-of-mass.readthedocs.io
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