Chiara Scuotto, Emanuele Marsico, Stefano Triberti


Initially, Emotional Intelligence (EI) was defined as an ability to process emotional information measurable through performance tasks. Later, other authors conceptualized EI as a set of aspects related to the recognition and regulation of emotions both in oneself and in others, that could be assessed through self-report instruments. Both performance tasks and self-report instruments present several problems. AI could support the assessment of EI by developing an algorithm that detects emotional states associated with facial expressions in response to viewing videos validated to induce specific emotions.  The project proposal aims to present a protocol that involves the use of an algorithm capable of comparing each subject's responses at the level of emotional states experienced. The project also includes the proposal of a comparative analysis of the quality and intensity of emotional states during the video, by monitoring some physiological parameters (HRV, GSR and temperature) through a biofeedback instrumentation. Based on the level of consistency among these data, the algorithm will provide a percentage related to the ability to recognize one's own emotions.


Emotional Intelligence, Biofeedback, Emotions, Artificial Intelligence, Emotion Recognition

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