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Automobile seats are developed in an iterative manner because subjective feedback, which is usually of questionable quality, drives the design. The time and cost associated with iteration could be justified if the process was guaranteed to produce a comfortable seat. Unfortunately, this is not the case. Current practices are based on the premise that seat system design teams need objective, measurable laboratory standards, which can be linked to subjective perceptions of comfort. Only in this way can predictions be made regarding whether or not a particular design will be viewed by the consumer as comfortable. This type of forecasting ability would effectively improve the efficiency with which automobile seats are designed. In this context, the research reported, developed, and validated a stepwise, multiple linear regression model relating seat interface pressure characteristics, occupant anthropometry, occupant demographics, and perceptions of seat appearance to an overall, subjective comfort index derived from a survey with proven levels of reliability and validity. The model performance statistics were: adjusted r(2)=0.668, standard error of estimate=2.308, F (6, 38)=15.728, p=0.000, and cross-validated r (15)=0.952, p=0.000. From the model, human criteria for seat interface pressure measures were established. These findings could not have been attained without first demonstrating that (1) the data collection protocol for seat interface pressure measurement was repeatable and (2) seat interface pressure measurements can be used to distinguish between seats.
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