The Affective Triad: Stimuli, Questionnaires, and Measurements

  • Simone Tognetti
  • Maurizio Garbarino
  • Matteo Matteucci
  • Andrea Bonarini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6975)


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 emotion emotion model video game stimuli self report physiology affective triad 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Simone Tognetti
    • 1
  • Maurizio Garbarino
    • 1
  • Matteo Matteucci
    • 1
  • Andrea Bonarini
    • 1
  1. 1.Dipartimento di Elettronica ed InformazionePolitecnico di Milano, IIT UnitMilanoItaly

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