The Anthropometrics of Disability - Designing Accessible Communities

dimensional databases which allow the development of true virtual human manikins with
disabilities and we do not have enough data on functional anthropometry. While there
have been many studies completed, Bradtmiller and Kozey and Das have demonstrated
that the results of these studies are not consistent. To generate the kinds of data needed
for human models is not a simple task. Interpolating data collected from the able -bodied
population is not advisable because there is enough information to indicate that the
anthropometry of people with disabilities is different, especially those who use wheeled
mobility devices.
These knowledge gaps define the agenda for the anthropometry of disability in the next
10-20 years:
• developing 3 -D databases,
• understanding the functional anthropometry of disability,
• collecting reliable and valid data, and
• organizing data into comprehensive and accessible databases.
In addition, there were several emerging research approaches that could provide
additional sources of information on human performance issues of relevance to accessible
and universal design.
DEVELOPI NG 3-D DATABASES
Three-dimensional anthropometric data can be collected in many ways. Mollenbroek
described several methods currently in use. The techniques available include traditional
manual measurement with anthropometric tools, full body scanning, photostereogrammetry,
video motion analysis, motion analysis using electromagnetic sensor
arrays and 3-D digitizing of landmarks. With photographic, video and scanning methods,
wheelchairs will obscure landmarks on the body. Data from electromechanical sensor
arrays are susceptible to distortion around metal. It is very difficult to collect 3-D data
using manual methods without the use of jigs or other apparatus.
Today, automated data collection is preferred in most cases due to the lower cost for
data entry and analysis. However, almost all the tools above require a dedicated
controlled setting to collect accurate data and the equipment is hard to move from place
to place. This limits access to large numbers of participants and increases the cost of data
collection because people with severe disabilities have limitations in mobility and need
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