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Modeling Variability in Torso Shape for Chair and Seat Design

[+] Author Affiliations
Matthew P. Reed

University of Michigan, Ann Arbor, MI

Matthew B. Parkinson

Pennsylvania State University, University Park, PA

Paper No. DETC2008-49483, pp. 561-569; 9 pages
  • ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1: 34th Design Automation Conference, Parts A and B
  • Brooklyn, New York, USA, August 3–6, 2008
  • Conference Sponsors: Design Engineering Division and Computers in Engineering Division
  • ISBN: 978-0-7918-4325-3 | eISBN: 0-7918-3831-5
  • Copyright © 2008 by ASME


Anthropometric data are widely used in the design of chairs, seats, and other furniture intended for seated use. These data are valuable for determining the overall height, width, and depth of a chair, but contain little information about body shape that can be used to choose appropriate contours for backrests. A new method is presented for statistical modeling of three-dimensional torso shape for use in designing chairs and seats. Laser-scan data from a large-scale civilian anthropometric survey were extracted and analyzed using principal component analysis. Multivariate regression was applied to predict the average body shape as a function of overall anthropometric variables. For optimization applications, the statistical model can be exercised to randomly sample the space of torso shapes for automated virtual fitting trials. This approach also facilitates trade-off analyses and other the application of other design decision-making methods. Although seating is the specific example here, the method is generally applicable to other designing for human variability situations in which applicable body contour data are available.

Copyright © 2008 by ASME
Topics: Design , Modeling , Shapes



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