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Comparison of Rarefication Techniques for Foot Simulation Using Subject Specific Three-Dimensional Anthropometry Data

机译:使用对象特定的三维人体测量学数据进行脚部仿真的反省技术的比较

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It is believed that one important extrinsic factor that causes foot deformity and pain was the footwear design. A good fit is one of the determinant design characteristics that determine the user's comfort. The fitness is not only geometric match between the shoe last and a static foot but also the fit during walking or running. With the availability of subject-specific three-dimensional foot data, it would be possible to construct a foot surface model for the specific subject and to use the model as a quick and intuitive tool for evaluation of the fitness of a shoe. In this paper, we used subject-specific three-dimensional anthropometry data to build static foot surface model and applied forward kinematics into the foot model to drive it. The static model allows the fitness test of shoe for one time try on, while the dynamic model allows evaluation of the fitness during walking or other activities (with shoe model and gait information given). The anthropometry data were firstly rarefied to ensure the efficiency of data processing. The reduced dataset was further segmented into phalanges using the marker points at the joints of the foot. Finally, the foot surface model was constructed and driven phalanx by phalanx to imitate the movement of human beings. Data rarefication problem was specifically addressed in this paper since it was an art to balancing the data accuracy and the computation efficiency. In total, six rarefication techniques were compared based on three principles: the calculation speed, the visualization effect, and the volume of the specific phalanx. The arch-height technique was selected as the most suitable technique for the reduction of foot anthropometry dataset.
机译:人们认为,引起足部畸形和疼痛的一个重要的外在因素是鞋类设计。良好的贴合度是决定用户舒适度的决定性设计特征之一。适应性不仅是鞋last和静态脚之间的几何匹配,而且是步行或跑步时的合脚性。利用特定于对象的三维足部数据,有可能为特定对象构建足部表面模型,并将该模型用作评估鞋子是否合适的快速直观工具。在本文中,我们使用特定于对象的三维人体测量学数据来构建静态脚表面模型,并将正向运动学应用到脚模型中来驱动它。静态模型允许一次试穿鞋子的适应性测试,而动态模型允许评估步行或其他活动过程中的适应性(给出鞋子模型和步态信息)。人体测量学数据首先被稀少以确保数据处理的效率。使用脚部关节处的标记点,将简化后的数据集进一步细分为指骨。最终,建立了足部表面模型,并通过趾骨驱动趾骨来模仿人类的运动。由于这是一种平衡数据准确性和计算效率的技术,因此本文专门解决了数据稀疏问题。总共根据三种原理比较了六种稀疏化技术:计算速度,可视化效果和特定指节的体积。选择弓高技术作为减少脚部人体测量数据集的最合适技术。

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