Assessing the accuracy of peak and cumulative low back analyses when human anthropometry is scaled in a virtual environment.

Date of Award


Publication Type

Master Thesis

Degree Name





Engineering, Automotive.



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.


This study addressed the effect of scaling subjects in a virtual reality environment when performing ergonomic evaluations for assembly automotive tasks. Ten male and ten female automotive employees participated in this study. Subjects were selected to fit into one of 4 anthropometric groups (n=5/group); 5th percentile female (5F), 50th percentile female (50F), 50th percentile male (50M), or 95th percentile male (95M). Each subject was asked to perform 3 automotive assembly tasks while interacting with a digital rendering of a vehicle in virtual reality. The subjects were represented in virtual reality as a human manikin (Classic Jack, UGS) whose actions were driven by their actual motions captured via motion tracking (EvaRT, MotionAnalysis). Each subject performed the tasks under 4 different conditions; in one condition, the subject appeared as their true size, and in the three other conditions, they were scaled to appear as the size of the other three subject groups. (Abstract shortened by UMI.) Source: Masters Abstracts International, Volume: 44-03, page: 1426. Thesis (M.H.K.)--University of Windsor (Canada), 2005.