Decision-Making for Product Form Image Based on ET-EEG Technology Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.3390/app152010979
The use of neurophysiological data to acquire product image avoids the inherent subjectivity in the empirical design process. In this paper, we use eye tracking–electroencephalography (ET-EEG) to study mapping among user behaviour, eye movements, EEG features and image decisions in the process of product form cognition. First, we designed an ET-EEG experiment using hair dryer stimuli, with morphology rated on a Likert scale. Then, ET-EEG data were categorized according to image category: “unambiguous (matching)”, “unambiguous (mismatching)”, “ambiguous (positive)”, or “ambiguous (negative)”. Finally, the behavioural data, eye movement indicators, and event-related potentials (ERPs) were analysed to parse the cognitive features. The behavioural, ET and ERP data were highly consistent, and their values increased as the cognition resources devoted to decision-making increased. ET-EEG physiological data thus objectively and effectively reflected users’ image cognition of products, providing theoretical support for design research on the origin of cognition.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app152010979
- https://www.mdpi.com/2076-3417/15/20/10979/pdf?version=1760351779
- OA Status
- gold
- References
- 31
- OpenAlex ID
- https://openalex.org/W4415130014
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4415130014Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/app152010979Digital Object Identifier
- Title
-
Decision-Making for Product Form Image Based on ET-EEG TechnologyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-10-13Full publication date if available
- Authors
-
Hao Shi, Shutao Zhang, Qinwei Zhang, Shifeng Liu, Kai QiuList of authors in order
- Landing page
-
https://doi.org/10.3390/app152010979Publisher landing page
- PDF URL
-
https://www.mdpi.com/2076-3417/15/20/10979/pdf?version=1760351779Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2076-3417/15/20/10979/pdf?version=1760351779Direct OA link when available
- Cited by
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0Total citation count in OpenAlex
- References (count)
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31Number of works referenced by this work
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