Anna Esposito, Department of Psychology and the International Institute for Advanced Scientific Studies (IIASS), Università della Campania “Luigi Vanvitelli”, Italy (firstname.lastname@example.org); Antonietta M. Esposito, Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Napoli Osservatorio Vesuviano, Napoli, Italy (email@example.com); Gennaro Cordasco, Department of Psychology and the International Institute for Advanced Scientific Studies (IIASS), Università della Campania “Luigi Vanvitelli”, Italy (firstname.lastname@example.org); Nelson Mauro Maldonato, Dipartimento di Neuroscienze and Reproductive Odontostomatological Sciences, Università di Napoli “Federico II”, Napoli, Italy (email@example.com); Francesco Carlo Morabito, Università degli Studi “Mediterranea” di Reggio Calabria, Italy (firstname.lastname@example.org); Vincenzo Paolo Senese, Department of Psychology and the International Institute for Advanced Scientific Studies (IIASS), Università della Campania “Luigi Vanvitelli”, Italy (email@example.com); Carl Vogel, Department of computer Science, Trinity Centre for Computing and Language Studies of Trinity College, Dublin, Ireland (firstname.lastname@example.org).
The themes of this special session are multidisciplinary in nature and closely connected in their final aims to identify features from a realistic dynamic of signal exchanges. Such dynamics characterize formal and informal social signals, communication modes, hearing and vision processes, and brain functionalities. Of particular interest are analyses of visual, written and audio information and corresponding computational efforts to automatically detect and interpret their semantic and pragmatic contents. Related applications of these interdisciplinary facets are ICT interfaces able to detect health and affective states of their users, interpret their psychological and behavioural patterns and support them through positively designed interventions to improve their quality of life.
Topics include but are not limited to:
- Signals for detecting affective wellbeing and emotional states
- Detection of health and psychological states from multimodal signals
- Social networks for information spread and share
- Empathic ICT interfaces
- Computational Architectures for Affective Systems
- Supervised and Unsupervised Learning Algorithms in Affective Systems
- Human and/or machine encoding and decoding of behavioural patterns
- Human daily cognitive activities