Developing original quantitative tools for emotion recognition has become one of the most fashionable topic in psychological research. In this work we present results from a pilot study aiming at identifying emotions through psychophysiological responses to visual stimuli chosen from a new database of affective pictures.
Limitations of available databases (e.g, IAPS, GAPED) have been extensively discussed in Marchewka et al. (2013).
In order to construct a database made up of pictures rated by a sample of participants representative of the general population, we have built an online questionnaire of 80 visual stimuli, posted on the Internet via social media sites and promoted by word of mouth.
Out of the 309 respondents, only 198 (127 females and 71 males, mean age 29.45, ranging from 18 to 62 years) evaluated at least 40 pictures; on average 173 ratings have been collected for each picture. Finally, 20 stimuli consistently rated by subjects have been selected. These stimuli will be used in the experimental sessions and will be made available upon request.In the literature, there is a lack of affective picture database specifically suited to investigate emotional response in children. The database Anger- and Fear-Eliciting Stimuli for Children (AFES-C) of affective stimuli aims at inducing experiences of 3 target emotions (neutral, anger, and fear) and could be used in experimental session involving children. To realize the database, a total of 84 children participating in the study were asked to (a) indicate the perceived emotion and its intensity and (b) rate the three affective dimensions of the Self-Assessment Manikin (SAM). Based on agreement between labeled and expected target emotion, the authors decided to select 15 stimuli to be included in the final dataset. Multivariate modeling techniques were applied to integrate categorical and dimensional representations of emotions. Hence, the proposed stimuli are characterized according to both these theoretical models of emotions.
We evaluated the factor structure and psychometric properties of the Italian version of the Disgust Propensity and Sensitivity Scale-Revised (DPSS-R, 16 items) in two samples taken from the general population. Exploratory factor analysis for ordinal Likert-type data supported the presence of four underlying factors: self-focused disgust, disgust propensity, somatic anxiety and disgust sensitivity. In the confirmatory analysis, the application of a bifactor model supported the presence of these four specific factors, along with a a general factor, providing a measure of disgust susceptibility.