Projection of anthropometric correlation for virtual population modelling Online publication date: Fri, 27-Apr-2018
by John Rasmussen; Rasmus Plenge Waagepetersen; Kasper Pihl Rasmussen
International Journal of Human Factors Modelling and Simulation (IJHFMS), Vol. 6, No. 1, 2018
Abstract: A new statistical method for generation of virtual populations based on anthropometric parameters is developed. The method addresses the problem that most anthropometric information is reported in terms of summary data such as means and standard deviations only, while the underlying raw data, and therefore the correlations between parameters, are not accessible. This problem is solved by projecting correlation from a data set for which raw data are provided. The method is tested and validated by generation of pseudo females from males in the ANSUR anthropometric dataset. Results show that the statistical congruency of the pseudo population with an actual female population is more than 90% for more than 90% of the possible parameter pairs. The method represents a new opportunity to generate virtual populations for specific geographic regions and ethnicities based on summary data only.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Human Factors Modelling and Simulation (IJHFMS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook