Estimating Affective Taste Experience Using Combined Implicit Behavioral and Neurophysiological Measures

article






Brouwer, A.M.

Broek, T.J. van den

Hogervorst, M.A.

Kaneko, D.

Toet, A.

Kallen, V.

Erp, J.B.F. van
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. (C) 2010-2012 IEEE.
Topics












BeveragesPhysiologyAffect sensing and analyticBehavioral measuresBehavioral responseCustomer experienceCustomer experience measurementNeurophysiological measuresNonverbal synthesisNonverbalsPhysiological measuresTastingPhysiological models
TNO Identifier
984365
Repository link
https://resolver.tno.nl/uuid:3becd1dd-a7e4-4802-880d-fdc5d6c3ae95
ISSN
19493045
Source
IEEE Transactions on Affective Computing, 14(1), pp. 849-856.
Pages
849-856
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