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具有头发下头皮形状可变性表示的三维参数成人头模型。

A three-dimensional parametric adult head model with representation of scalp shape variability under hair.

机构信息

University of Michigan, USA.

Marine Corps Systems Command, USA.

出版信息

Appl Ergon. 2021 Jan;90:103239. doi: 10.1016/j.apergo.2020.103239. Epub 2020 Aug 26.

DOI:10.1016/j.apergo.2020.103239
PMID:32861089
Abstract

Modeling the shape of the scalp and face is essential for the design of protective helmets and other head-borne equipment. However, head anthropometry studies using optical scanning rarely capture scalp shape because of hair interference. Data on scalp shape is available from bald men, but female data are generally not available. To address this issue, scalp shape was digitized in an ethnically diverse sample of 100 adult women, age 18-59, under a protocol that included whole head surface scanning and scalp measurement using a three-dimensional (3D) coordinate digitizer. A combined male and female sample was created by adding 3D surface scans of a similarly diverse sample of 80 bald men. A statistical head shape model was created by standardizing the head scan data. A total of 58 anatomical head landmarks and 12 head dimensions were obtained from each scan and processed along with the scans. A parametric model accounting for the variability of the head shape under the hair as a function of selected head dimensions was developed. The full-variable model has a mean shape error of 3.8 mm; the 95th percentile error was 7.4 mm, which were measured at the vertices. The model will be particularly useful for generating a series of representing a target population as well as for generating subject-specific head shapes along with predicted landmarks and dimensions. The model is publicly available online at http://humanshape.org/head/.

摘要

头皮和面部形态建模对于防护头盔和其他头部佩戴设备的设计至关重要。然而,由于头发的干扰,使用光学扫描进行的头部人体测量研究很少能捕捉到头皮的形状。头皮形状的数据可从光头男性中获得,但通常无法获得女性的数据。为了解决这个问题,在一项包括对头表面进行全面扫描以及使用三维(3D)坐标数字化仪对头皮进行测量的方案下,对 100 名年龄在 18 至 59 岁之间的成年女性进行了头皮形态数字化研究。该研究的参与者来自不同种族。通过添加 80 名具有类似多样性的光头男性的 3D 头部表面扫描,创建了一个男女混合样本。通过标准化头部扫描数据创建了一个统计头部形状模型。从每个扫描中获得了 58 个解剖学头部标志点和 12 个头部尺寸,并与扫描一起进行处理。开发了一个参数模型,该模型将头发下头部形状的可变性作为选定头部尺寸的函数进行了说明。全变量模型的平均形状误差为 3.8 毫米;95%的误差为 7.4 毫米,这是在顶点处测量的。该模型将特别有助于生成一系列代表目标人群的头部形状,以及生成具有预测标志点和尺寸的特定于个体的头部形状。该模型可在 huma nshape.org/head/ 上公开获取。

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