Synthetic Facial Emotional Expression Recognition in People with Depressive Symptoms

Considering the exploitation of virtual agents in Information and Communication Technologies (ICT)-based interventions for mental health, it is necessary to investigate the underlying characteristics of their interactions with users experiencing mental health issues, like depression. Existing literature highlights an impaired ability to process emotional stimuli in depression. While numerous studies have examined how individuals with depression decode emotional expressions displayed by humans, the ability to recognize synthetic emotional expressions conveyed by virtual agents among this population has received limited empirical attention. Thus, this study aims to expand the available knowledge on facial recognition of synthetic emotional expressions in individuals with depressive symptoms, potentially contributing to the advancement of ICT-based mental health interventions by tailoring services to better meet users' specific needs.