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| Principal Component Analysis and Mesh Morphing Algorithm |
| SHI Xiang-nan1, 2, HE Yu-hao3 |
1.School of Transportation and Vehicle Engineering, Shandong University of Technology, Shandong Province Zibo 266590, China;
2.University of Michigan Transportation Research Institute, Ann Arbor, Michigan, USA;
3.Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, USA |
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Abstract The susceptibility of the clavicle to injury underscores its role as an important loading path during both frontal impact and side impact crashes, since clavicle is loaded directly by shoulder belt in frontal impact and through shoulder in lateral impact crashes. This study aims to developing a parametric clavicle finite element model capable of simulating impact responses with different parameters. A statistical clavicle geometry model was developed based on computed tomography (CT) scans from 89 subjects using principal component analysis (PCA) and multivariate regression analysis. Using this statistical clavicle geometry model and mesh morphing method developed in this study, a series of detailed 3D clavicle geometries were predicted by age, gender, and length of the bone, all of which showed strong effects on clavicle geometry. After assigning material properties and validation process, this parametric model developed in this study can be used to investigate the effects of age, gender and length at the same time.
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Received: 05 October 2017
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| Fund:University of Michigan Transportation Research Institute and Shandong Provincial Innovation Foundation for Post-doctoral; grant number: 2017035. |
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Corresponding Authors:
SHI Xiang-nan. E-mail: xiangnanshi@163.com
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