Preliminary study of the perception of emotions expressed by virtual agents in the context of Parkinson's disease

Abstract

In the context of Parkinson's disease, this preliminary work aims to study the recognition profiles of emotional faces, dynamically expressed by virtual agents in a Healthy Control (HC) population. In this online experiment, users had to watch 56 trials of two-second animations, showing an emotion progressively expressed by an avatar and then indicate the recognized emotion by clicking a button. 211 participants completed this experiment online as HC. Of the demographics variables, only age influenced negatively recognition accuracy in HC. The intensity of the expression influenced accuracy as well. Interaction effects between gender, emotion, intensity, and avatar gender are also discussed. The results of four patients with Parkinson's Disease are presented as well. Patients tended to have lower recognition accuracy than age-matched HC (59% for age-matched HC; 45.1% for patients). Joy, sadness and fear seemed less recognized by patients.