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ANFIS modeling for predicting affective responses to tactile textures
Author(s) -
Akay Diyar,
Chen Xiaojuan,
Barnes Cathy,
Henson Brian
Publication year - 2011
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20268
Subject(s) - adaptive neuro fuzzy inference system , inference system , feeling , texture (cosmology) , computer science , artificial intelligence , surface finish , psychology , fuzzy logic , engineering , fuzzy control system , social psychology , mechanical engineering , image (mathematics)
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. © 2011 Wiley Periodicals, Inc.