ANFIS modeling for predicting affective responses to tactile textures

  • Diyar Akay
  • , Xiaojuan Chen
  • , Cathy Barnes
  • , Brian Henson

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)269-281
Number of pages13
JournalHuman Factors and Ergonomics in Manufacturing and Service Industries
Volume22
Issue number3
DOIs
Publication statusPublished - May 2012
Externally publishedYes

Keywords

  • ANFIS
  • Affective engineering
  • Feeling
  • Semantic
  • Tactile texture

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