Modeling variability in torso shape for chair and seat design

Matthew P. Reed, Matthew B. Parkinson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Title of host publicationASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008
Pages561-569
Number of pages9
EditionPARTS A AND B
DOIs
StatePublished - Dec 1 2008
EventASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008 - Brooklyn, NY, United States
Duration: Aug 3 2008Aug 6 2008

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
NumberPARTS A AND B
Volume1

Other

OtherASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008
CountryUnited States
CityBrooklyn, NY
Period8/3/088/6/08

Fingerprint

Seats
Modeling
Principal component analysis
Decision making
Multivariate Regression
Lasers
Statistical Modeling
Principal Component Analysis
Statistical Model
Choose
Trade-offs
Decision Making
Laser
Predict
Three-dimensional
Design
Optimization
Statistical Models

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Cite this

Reed, M. P., & Parkinson, M. B. (2008). Modeling variability in torso shape for chair and seat design. In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008 (PARTS A AND B ed., pp. 561-569). (Proceedings of the ASME Design Engineering Technical Conference; Vol. 1, No. PARTS A AND B). https://doi.org/10.1115/DETC2008-49483
Reed, Matthew P. ; Parkinson, Matthew B. / Modeling variability in torso shape for chair and seat design. ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008. PARTS A AND B. ed. 2008. pp. 561-569 (Proceedings of the ASME Design Engineering Technical Conference; PARTS A AND B).
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abstract = "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.",
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Reed, MP & Parkinson, MB 2008, Modeling variability in torso shape for chair and seat design. in ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008. PARTS A AND B edn, Proceedings of the ASME Design Engineering Technical Conference, no. PARTS A AND B, vol. 1, pp. 561-569, ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008, Brooklyn, NY, United States, 8/3/08. https://doi.org/10.1115/DETC2008-49483

Modeling variability in torso shape for chair and seat design. / Reed, Matthew P.; Parkinson, Matthew B.

ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008. PARTS A AND B. ed. 2008. p. 561-569 (Proceedings of the ASME Design Engineering Technical Conference; Vol. 1, No. PARTS A AND B).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Reed MP, Parkinson MB. Modeling variability in torso shape for chair and seat design. In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2008. PARTS A AND B ed. 2008. p. 561-569. (Proceedings of the ASME Design Engineering Technical Conference; PARTS A AND B). https://doi.org/10.1115/DETC2008-49483