222
Views
4
CrossRef citations to date
0
Altmetric
Articles

Finite element modelling of Chinese male office workers’ necks using 3D body measurements

, &
Pages 766-775 | Received 16 Nov 2015, Accepted 02 May 2016, Published online: 21 May 2016
 

Abstract

Recognizing the influence of occupational habits on human morphology, there has been a discernible increase in research taking anthropometric body measurements of a target population for the purpose of customized product development and production to meet different customer needs. This study aims to develop a 3D neck model for the Chinese young male office workers with a goal to provide a tool to maximize the ergonomic fit and comfort of the collar part of apparel products. A total of 200 male Chinese office workers meeting the sampling criteria were recruited for this study. Using factor analysis, the raw 3D measurements were reduced to a six-factor seven-measure model, capturing majority of the neck structure information. Based on these 7 neck measurements, the 200 subjects were classified through K means cluster analysis into 4 clusters. The cluster with largest number of subjects was chosen for the 3D neck model development. This 3D model includes three layers: the skin layer, the soft tissue layer and the skeleton layer. Comparing to 2D neck models, this three-layer 3D neck model provides a better and closer imitation of real human necks, permitting simulation and investigation of the pressure-deformation process that a neck experiences during wearing.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 268.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.