A Social Interaction Interface Supporting Affective Augmentation Based on Neuronal Data

Abstract

In this demonstration we present a prototype for an avatar-mediated social interaction interface that supports the replication of head- and eye movement in distributed virtual environments. In addition to the retargeting of these natural behaviors, the system is capable of augmenting the interaction based on the visual presentation of affective states. We derive those states using neuronal data captured by electroencephalographic (EEG) sensing in combination with a machine learning driven classification of emotional states.