Biomedical and Life Sciences Division, CFD Research Corporation, Huntsville, AL, United States of America.
Voiland School of Chemical Engineering and Bioengineering, Department of Integrative Physiology and Neuroscience, Washington State University, Pullman, WA, United States of America.
PLoS One. 2020 Jan 28;15(1):e0219954. doi: 10.1371/journal.pone.0219954. eCollection 2020.
A new methodology was developed to quickly generate whole body models with detailed neck musculoskeletal architecture that are properly scaled in terms of anthropometry and muscle strength. This method was implemented in an anthropometric model generation software that allows users to interactively generate any new male or female musculoskeletal models with adjustment of anthropometric parameters (such as height, weight, neck circumference, and neck length) without the need of subject-specific motion capture or medical images. 50th percentile male and female models were developed based on the 2012 US Army Anthropometric Survey (ANSUR II) database and optimized with a novel bilevel optimization method to have strengths comparable to experimentally measured values in the literature. Other percentile models (ranging from the 1st to 99th percentile) were generated based on anthropometric scaling of the 50th percentile models and compared. The resultant models are reasonably accurate in terms of both musculoskeletal geometry and neck strength, demonstrating the effectiveness of the developed methodology for interactive neck model generation with anthropometric scaling.
开发了一种新的方法学，用于快速生成具有详细颈部肌肉骨骼结构的全身模型，这些模型在人体测量学和肌肉力量方面进行了适当的缩放。该方法被实施在人体测量模型生成软件中，允许用户通过调整人体测量参数（如身高、体重、颈围和颈长）来交互式地生成任何新的男性或女性肌肉骨骼模型，而无需进行特定于主题的运动捕捉或医学图像。基于 2012 年美国陆军人体测量调查（ANSUR II）数据库开发了 50 百分位男性和女性模型，并使用新的双层优化方法进行了优化，以使其强度与文献中实验测量值相当。其他百分位模型（从第 1 百分位到第 99 百分位）是基于 50 百分位模型的人体测量缩放生成的，并进行了比较。生成的模型在肌肉骨骼几何形状和颈部强度方面都具有相当的准确性，证明了所开发的方法学用于具有人体测量缩放的交互式颈部模型生成的有效性。
