Multi-modal emotion-related data collection within a virtual earthquake emulator

The collection of emotion-related signals, such as face video sequences, speech utterances, galvanic skin response, and blood pressure from pupils in a virtual reality environment, when the pupils attempt to evacuate a school during an earthquake, is addressed in this paper. We assess whether pupils’ spontaneous emotional state can be accurately recognized, using classifiers trained on elicited emotional speech and videos.