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|Title: ||'Design for all': methods and data to support designers|
|Authors: ||Sims, Ruth|
|Issue Date: ||2003|
|Publisher: ||© Ruth Elise Sims|
|Abstract: ||If designers are to meet the needs of the growing population of older and disabled people then data
on size, shape, posture and capabilities will be increasingly important. This thesis details a
methodology for the collection of anthropometry, joint constraints, reach range, postural capability
and task specific information, to create a unique database of `individuals'. These data were then
used in the development of a computer-based design tool (HADRIAN), to allow design
professionals to estimate the percentage of people who could be accommodated by a design.
Having complete data sets for individuals is vital to enable multivariate analysis, as opposed to
traditional univariate percentile data.
Following a review of the literature two interview surveys were conducted with 32 design
professionals and 50 older and disabled people. The majority of designers were aware of the
philosophy of `design for all', but rarely considered the approach due to perceived time and
financial costs. With respect to older and disabled people it was found that nearly all experienced
problems completing basic activities of daily life, and that improvements to existing designs could
improve quality of life. Activities such as being able to cook a meal, and use the bath were
reported as being particularly important.
Firstly, a pilot study was conducted with 8 participants to assess the different data collection
options. Data were then collected on 100 people, with the majority being older and/or disabled,
and encompassing a wide range of capabilities. From these data it was possible to see that the
anthropometric data showed a range beyond 15` and 99`h percentile for each dimension when
compared to existing anthropometry data, and a breadth of variation in task specific behaviours.
Validation trials were then conducted to compare the actual task performance of 10 of the 100
`individuals' with that predicted by HADRIAN, with postures and task capabilities being correctly
predicted for open-access reach-and-lift tasks. This gives some confidence that it is possible to
predict postures and capabilities from the data collected.|
|Description: ||A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.|
|Appears in Collections:||PhD Theses (Design School)|
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