Affective Computing has always aimed to answer the question: which measurement is most suitable to predict the subject’s affective state? Many experiments have been devised to evaluate the relationships among three types of variables (the affective triad): stimuli, self-reports, and measurements. Being the real affective state hidden, researchers have faced this question by looking for the measure most related either to the stimulus, or to self-reports. The first approach assumes that people receiving the same stimulus are feeling the same emotion; a condition difficult to match in practice. The second approach assumes that emotion is what people are saying to feel, and seems more likely. We propose a novel method, which extends the mentioned ones by looking for the physiological measurement mostly correlated to the self-report due to emotion, not the stimulus. This guarantees to find a measure best related to subject’s affective state.

The Affective Triad: Stimuli, Questionnaires, and Measurements

TOGNETTI, SIMONE;GARBARINO, MAURIZIO;MATTEUCCI, MATTEO;BONARINI, ANDREA
2011-01-01

Abstract

Affective Computing has always aimed to answer the question: which measurement is most suitable to predict the subject’s affective state? Many experiments have been devised to evaluate the relationships among three types of variables (the affective triad): stimuli, self-reports, and measurements. Being the real affective state hidden, researchers have faced this question by looking for the measure most related either to the stimulus, or to self-reports. The first approach assumes that people receiving the same stimulus are feeling the same emotion; a condition difficult to match in practice. The second approach assumes that emotion is what people are saying to feel, and seems more likely. We propose a novel method, which extends the mentioned ones by looking for the physiological measurement mostly correlated to the self-report due to emotion, not the stimulus. This guarantees to find a measure best related to subject’s affective state.
Affective Computing and Intelligent Interaction
9783642245701
affective computing; emotion; emotion model; video game; stimuli; self report; physiology; affective triad
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/608365
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