• DocumentCode
    2603749
  • Title

    A Multiple Regression Model for Predicting Comfort Sensation of Knitted Fabric in Sports Condition Based on Objective Properties

  • Author

    Li, Min ; Li, Dong-Ping ; Zhang, Wei-Yuan ; Tang, Xiao-Zhong

  • Author_Institution
    Fashion Design & Eng. Dept., Donghua Univ., Shanghai, China
  • Volume
    3
  • fYear
    2009
  • fDate
    21-22 May 2009
  • Firstpage
    372
  • Lastpage
    375
  • Abstract
    Clothing comfort is a state of satisfaction indicating physiological, psychological and physical balance among the person. Though objective experiments are easy to measure, subjective experiment is rated an end-use performance test to collect the comfort sensation of wears. In this paper, objective and subjective experiment have been done with 20 knitted fabric samples. Objective experiments includes thermal insulation, touch feeling of warm or cool Q-max, air permeability, water-vapor permeability, wicking, moisture regain rate, evaporation rate experiment. Subjective experiment with four processes is taken and questionnaire is designed to test comfort sensation of knitwear fabric. Based on experimental data, a multiple regression model for predicting comfort sensations of knitted fabric in sports condition with objective properties is established.
  • Keywords
    ergonomics; evaporation; fabrics; moisture; permeability; regression analysis; sportswear; air permeability; clothing comfort; comfort sensation prediction; evaporation rate; knitted fabric; moisture regain rate; multiple regression model; objective properties; sports; thermal insulation; water-vapor permeability; Clothing; Cotton; Fabrics; Insulation; Permeability; Predictive models; Psychology; Testing; Thermal resistance; Yarn; comfort sensation; factor; knitted fabric; multiple regression; objective property;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Computing Science, 2009. ICIC '09. Second International Conference on
  • Conference_Location
    Manchester
  • Print_ISBN
    978-0-7695-3634-7
  • Type

    conf

  • DOI
    10.1109/ICIC.2009.299
  • Filename
    5168882