Education, Science, Technology, Innovation and Life
Open Access
Sign In

Identification of Preferred Product Image under the Visual Cognitive Neural Mechanism

Download as PDF

DOI: 10.23977/icmit.2018.037

Author(s)

Yang Chen, Li Lin, Zhiang Chen

Corresponding Author

Li Lin

ABSTRACT

In order to improve the objectivity of the measurement of preferred product image, eye-tracking combined with EEG technology was used to locate users' preferred image of products. The method included the following steps: (1) Product samples and image words of the subjects as stimuli materials were imported into the computer's picture viewing module, which displayed the product samples or image words; (2) Participants watched the stimuli materials; (3) Eye movements and EEG data were collected by telemetry eye-tracker and electroencephalograph according to the reaction of participants when they watched the stimuli materials; (4) Preferred image was obtained by comprehensive evaluation of the average gaze duration of eye movements data and the asymmetry index of frontal alpha of EEG data. The experimental results show that the image words of “Complex-Concise”, “Retro-Modern”, “Smart-Heavy”, “Lively-Serious” caused participant's average gaze duration to be shorter than other words. Moreover, the power of alpha waves captured by the left frontal channel (F3) was significantly lower than the average power of the alpha waves captured by the right frontal channel (F4) when participants observed the image words of “Concise”, “Gorgeous”, “Modern”, “Smart”, “Lively”. It shows that user's preferred image of perceptual products can be obtained more scientifically and effectively by using the combined physiological measurement technologies of eye-tracking and EEG, and reference can be provided for design applications based on user's preferred image in silver jewelry.

KEYWORDS

Eye-tracking technology, EEG technology, perceptual image, preferred image

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.