ANFIS modeling for predicting affective responses to tactile textures

AKAY D., Chen X., Barnes C., Henson B.

HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES, cilt.22, sa.3, ss.269-281, 2012 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 3
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1002/hfm.20268
  • Dergi Adı: HUMAN FACTORS AND ERGONOMICS IN MANUFACTURING & SERVICE INDUSTRIES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.269-281
  • Anahtar Kelimeler: Tactile texture, Affective engineering, Feeling, Semantic, ANFIS, FUZZY INFERENCE SYSTEM, ROUGH SETS MODEL, PRODUCT DESIGN, USER SATISFACTION, NEURAL-NETWORKS, FORM DESIGN, PERCEPTION, LOGIC, NEEDS, REQUIREMENTS
  • Hacettepe Üniversitesi Adresli: Hayır

Özet

The Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed to simulate and analyze the mapping between the physical properties of tactile textures and people's affective responses. People were asked to rate the tactile feeling of 37 tactile textures against six pairs of adjectives on a semantic differential questionnaire. The friction coefficient, average roughness, compliance, and a thermal parameter of each tactile texture were measured. ANFIS models were built to predict the affective responses to tactile textures. The resulting ANFIS models demonstrated a good match between predicted and actual responses, and always yielded better performance when compared to linear and exponential regression models. The effects of physical properties of textures on affective responses were also analyzed by simulating the synthetic data with ANFIS. (C) 2011 Wiley Periodicals, Inc.