期刊
JOURNAL OF BIOMECHANICS
卷 47, 期 10, 页码 2277-2285出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jbiomech.2014.04.045
关键词
Rib cage geometry; Principal component analysis; Regression; Vulnerable populations
资金
- U.S. National Science Foundation [1300815]
- State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body at Hunan University
- Hunan Provincial Innovation Foundation for Postgraduate from China
- Directorate For Engineering [1300815] Funding Source: National Science Foundation
- Div Of Civil, Mechanical, & Manufact Inn [1300815] Funding Source: National Science Foundation
In this study, we developed a statistical rib cage geometry model accounting for variations by age, sex, stature and body mass index (BMI). Thorax CT scans were obtained from 89 subjects approximately evenly distributed among 8 age groups and both sexes. Threshold-based CT image segmentation was performed to extract the rib geometries, and a total of 464 landmarks on the left side of each subject's ribcage were collected to describe the size and shape of the rib cage as well as the cross-sectional geometry of each rib. Principal component analysis and multivariate regression analysis were conducted to predict rib cage geometry as a function of age, sex, stature, and BMI, all of which showed strong effects on rib cage geometry. Except for BMI, all parameters also showed significant effects on rib cross-sectional area using a linear mixed model. This statistical rib cage geometry model can serve as a geometric basis for developing a parametric human thorax finite element model for quantifying effects from different human attributes on thoracic injury risks. (C) 2014 Elsevier Ltd. All rights reserved.
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