Emerging Trends in Affective Computing and Measuring Emotional Intelligence

Dear Colleagues,

Affective computing is a field at the intersection of psychology and computer science, which fully takes into account the analysis of exposed human emotions through various bioinformatic dimensions, such as Facial Expression Recognition (Dynamic/Micro), Speech Expression Recognition, Multi-modal Expression Recognition, and physiological electrical signals (including EEG/ECG/MEG). Although current computational techniques for emotion recognition are based on Artificial Intelligence, in order to reveal emotions more accurately, researchers are focusing on how to further integrate psychology and neuroscience. Their goal is to improve the precision of emotion recognition in emotion categorization and diversify the types of emotions identified, and they are trying to apply computational emotion successfully to daily life.

With this in mind, this Special Issue proposes a call for papers with cutting-edge, multidisciplinary approaches at the intersection of affective computing and measuring emotional intelligence, with a focus on research that includes, but is not limited to, the following:

• Emerging theories, methods, and applications of measuring emotional intelligence with AI technology, including, but not limited to, self-awareness, self-management, self-motivation, empathy, and social skills, which form the core of humans’ ability to understand and cope with emotions and relationships.
• Emerging theories, methods, and applications of emotional study integrating psychology and AI.
• Emerging theories, methods, and applications of Dynamic Facial Expression Recognition, Micro-expression Recognition, Action Unit Detection, Speech Emotional Recognition, Multi-modal Emotion Recognition, and bio-signal emotion recognition (EEG/ECG/MEG, etc.). 

Methodological and technical research on AI measurement techniques for emotional disorders related to computational psychology and computational psychiatry, such as the emotions of Loneliness, Depression and Anxiety, especially encouraging quantitative techniques.

You may choose our Joint Special Issue in Applied Sciences.

Dr. Feng Liu
Guest Editor

Manuscript Submission Information

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