Prediction of Car Design Perception Using EEG and Gaze Patterns

Seong Eun Moon, Jun Hyuk Kim, Sun Wook Kim, Jong Seok Lee

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


In this paper, we deal with the issue of implicit monitoring of perceptual responses to product design through electroencephalography (EEG) and eye tracking. Four evaluation factors, namely, preference, luxury, complexity, and harmony are considered to investigate how people perceive the car design. In particular, the quantified perceptual responses are predicted based on EEG and gaze data. Average root-mean-square errors of 0.210 and 1.215 are obtained from subject-dependent and subject-independent regressions on a 7-point score scale, respectively, which demonstrates that perception of car design can be predicted via implicit monitoring.

Original languageEnglish
Pages (from-to)843-856
Number of pages14
JournalIEEE Transactions on Affective Computing
Issue number4
Publication statusPublished - 2021

Bibliographical note

Publisher Copyright:
© 2010-2012 IEEE.

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction


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