• DocumentCode
    477965
  • Title

    A Study on Approaches to Estimate Body Dimensions: Stature as an Example

  • Author

    Chao, Wei-Cheng ; Wang, Eric Min-Yang

  • Author_Institution
    Dept. of Ind. Eng. & Eng. Manage., Nat. Tsing Hua Univ., Hsinchu
  • Volume
    4
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    531
  • Lastpage
    535
  • Abstract
    A large-scale anthropometric database [B. Das and A.K. Sengupta, 1996] was built in Taiwan in the late 1990s and was published in 2002. The procedures for collecting anthropometric data are usually complicated and costly in terms of resources such as workforce, time, and money. According to previous experiences and surveys among the designers and engineers, most practitioners do not know how the old anthropometric data may be converted into applicable new ones when updated data is unavailable [E.M. Wang et al., 1999]. Therefore, it is indeed a significant undertaking to develop methods that can easily convert old data into new ones easily especially with minimal errors. This study used statistical regression analysis and artificial neural networks (ANN) to estimate body dimensions and verified their effect. Subsequently, the estimation of stature built through stepwise regression was more accurate, convenient, and available compared to the other which was built through artificial neural networks.
  • Keywords
    anthropometry; biology computing; neural nets; regression analysis; artificial neural networks; body dimension estimation; large-scale anthropometric database; statistical regression analysis; stepwise regression; Artificial neural networks; Chaos; Data engineering; Databases; Design engineering; Equations; Fuzzy systems; Humans; Industrial engineering; Research and development management; Anthropometric data; Anthropometry; Artificial neural networks; Stepwise regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
  • Conference_Location
    Jinan Shandong
  • Print_ISBN
    978-0-7695-3305-6
  • Type

    conf

  • DOI
    10.1109/FSKD.2008.209
  • Filename
    4666442