Fibers and Polymers

, Volume 20, Issue 1, pp 199–209 | Cite as

Tactile Comfort Prediction of Functional Fabrics from Instrumental Data Using Intelligence Systems

  • Melkie Getnet TadesseEmail author
  • Yan Chen
  • Lichuan Wang
  • Vincent Nierstrasz
  • Carmen Loghin
Open Access


Subjective and objective evaluations of the handle of textile materials are very important to describe its tactile comfort for next-to-skin goods. In this paper, the applicability of artificial neural-network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) modeling approaches for the prediction of the psychological perceptions of functional fabrics from mechanical properties were investigated. Six distinct functional fabrics were evaluated using human subjects for their tactile score and total hand values (THV) using tactile and comfort-based fabric touch attributes. Then, the measurement of mechanical properties of the same set of samples using KES-FB was performed. The RMSE values for ANN and ANFIS predictions were 0.014 and 0.0122 and are extremely lower than the variations of the perception scores of 0.644 and 0.85 for ANN and ANFIS, respectively with fewer prediction errors. The observed results indicated that the predicted tactile score and THV are almost very close to the actual output obtained using the human judgment. Fabric objective measurement technology, therefore, provides reliable measurement approaches for functional fabric quality inspection, control, and design specification.


ANFIS ANN Mechanical properties Total hand value Tactile comfort 


Funding note: Open access funding provided by University of Boras.


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© The Author(s), corrected publication 2019 2019

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Melkie Getnet Tadesse
    • 1
    • 2
    • 3
    Email author
  • Yan Chen
    • 3
  • Lichuan Wang
    • 3
  • Vincent Nierstrasz
    • 2
  • Carmen Loghin
    • 1
  1. 1.Faculty of TextilesLeather & Industrial ManagementIasiRomania
  2. 2.Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and BusinessUniversity of BoråsBoråsSweden
  3. 3.The College of Textile and Clothing EngineeringSoochow UniversitySuzhouChina

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