Park Byoung-Keon, Reed Matthew P
a Biosciences Group, University of Michigan Transportation Research Institute , Ann Arbor , MI , USA.
b Center for Ergonomics, Industrial and Operations Engineering, University of Michigan , Ann Arbor , MI , USA.
Ergonomics. 2015;58(10):1714-25. doi: 10.1080/00140139.2015.1033480. Epub 2015 May 1.
A statistical body shape model (SBSM) for children was developed for generating a child body shape with desired anthropometric parameters. A standardised template mesh was fit to whole-body laser scan data from 137 children aged 3-11 years. The mesh coordinates along with a set of surface landmarks and 27 manually measured anthropometric variables were analysed using principal component (PC) analysis. PC scores were associated with anthropometric predictors such as stature, body mass index (BMI) and ratio of erect sitting height to stature (SHS) using a regression model. When the original scan data were compared with the predictions of the SBSM using each subject's stature, BMI and SHS, the mean absolute error was 10.4 ± 5.8 mm, and 95th percentile error was 24.0 ± 18.5 mm. The model, publicly available online, will have utility for a wide range of applications. Practitioner Summary: A statistical body shape model for children helps to account for inter-individual variability in body shapes as well as anthropometric dimensions. This parametric modelling approach is useful for reliable prediction of the body shape of a specific child with a few given predictors such as stature, body mass index and age.
开发了一种用于儿童的统计身体形状模型（SBSM），以生成具有所需人体测量参数的儿童身体形状。将标准化模板网格拟合到137名3至11岁儿童的全身激光扫描数据上。使用主成分（PC）分析对网格坐标以及一组表面标志和27个手动测量的人体测量变量进行分析。使用回归模型将PC分数与身高、体重指数（BMI）和直立坐高与身高之比（SHS）等人体测量预测指标相关联。当使用每个受试者的身高、BMI和SHS将原始扫描数据与SBSM的预测结果进行比较时，平均绝对误差为10.4±5.8毫米，第95百分位数误差为24.0±18.5毫米。该模型可在网上公开获取，将在广泛的应用中发挥作用。从业者总结：儿童统计身体形状模型有助于解释个体间身体形状以及人体测量尺寸的变异性。这种参数化建模方法对于使用身高、体重指数和年龄等一些给定预测指标可靠预测特定儿童的身体形状很有用。
