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/.

头皮和面部形状的建模对于防护头盔和其他头戴设备的设计至关重要。然而，由于头发干扰，使用光学扫描的头部人体测量学研究很少捕捉头皮形状。秃头男性可以获得头皮形状的数据，但女性数据通常无法获得。为了解决这个问题，根据包括使用三维 (3D) 坐标数字化仪进行整个头部表面扫描和头皮测量的协议，对 100 名年龄在 18-59 岁的不同种族女性样本中的头皮形状进行了数字化。通过添加 80 名秃头男性的类似多样化样本的 3D 表面扫描，创建了一个组合的男性和女性样本。通过标准化头部扫描数据创建统计头部形状模型。从每次扫描中获得总共 58 个解剖头部标志和 12 个头部尺寸，并与扫描一起处理。开发了一个参数模型，该模型将头发下的头部形状作为选定头部尺寸的函数。全变量模型的平均形状误差为 3.8 mm；第 95 个百分位误差为 7.4 毫米，这是在顶点处测量的。该模型对于生成一系列代表目标人群以及生成特定主题的头部形状以及预测的地标和尺寸特别有用。该模型可在 http://humanshape.org/head/ 在线公开获得。全变量模型的平均形状误差为 3.8 mm；第 95 个百分位误差为 7.4 毫米，这是在顶点处测量的。该模型对于生成一系列代表目标人群以及生成特定主题的头部形状以及预测的地标和尺寸特别有用。该模型可在 http://humanshape.org/head/ 在线公开获得。全变量模型的平均形状误差为 3.8 mm；第 95 个百分位误差为 7.4 毫米，这是在顶点处测量的。该模型对于生成一系列代表目标人群以及生成特定主题的头部形状以及预测的地标和尺寸特别有用。该模型可在 http://humanshape.org/head/ 在线公开获得。