Estimating Affective Taste Experience Using Combined Implicit Behavioral and Neurophysiological Measures

Estimating Affective Taste Experience Using Combined Implicit Behavioral and Neurophysiological Measures

We trained a model to distinguish an extreme high arousal, unpleasant drink from regular drinks based on a range of implicit behavioral and physiological responses to naturalistic tasting. The trained model predicted arousal ratings of regular drinks, highlighting the possibility to estimate affecti...

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Veröffentlicht in:IEEE transactions on affective computing 2023-01, Vol.14 (1), p.849-856
Hauptverfasser: Brouwer, A.-M., van den Broek, T. J., Hogervorst, M. A., Kaneko, D., Toet, A., Kallen, V., van Erp, J. B. F.
Format: Artikel
Sprache:eng
Schlagworte:
Affect sensing and analytics
Arousal
Atmospheric measurements
Current measurement
customer experience measurement
Electroencephalography
Heart rate
nonverbal synthesis
Organizations
Particle measurements
physiological measures
Physiological responses
Physiology
Ratings
tasting
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Beschreibung
Zusammenfassung:We trained a model to distinguish an extreme high arousal, unpleasant drink from regular drinks based on a range of implicit behavioral and physiological responses to naturalistic tasting. The trained model predicted arousal ratings of regular drinks, highlighting the possibility to estimate affective experience without having to rely on subjective ratings.
ISSN:1949-3045
1949-3045
DOI:10.1109/TAFFC.2020.3032236