Assessment of human response to robot facial expressions through visual evoked potentials

Abstract

The focus of this work is to investigate and quantify the ability of a humanoid `hybrid face' robot to effectively convey emotion to a human observer by mapping their physiological (EEG) response to perceived emotional information. Specifically, we examine the event related response during two implicit emotion recognition experiments to determine the modulation of the face-specific N170 brain response component to robot facial expressions. EEG recordings were taken from a range of test subjects observing the BERT2 robot cycle through a range of facial emotions in each emotion recognition experiment. Results from both experiments demonstrate that the stimuli evoke the N170 component and that digital facial expressions with high correlations can be discriminated. Emotional expressions evoke a larger response relative to neutral stimuli, with negative evoking an increased amplitude and latency to positive emotions, and demonstrate that the response to robot facial expressions evoke similar brain activity to that of a human emotions. This study is the first of its nature to investigate and quantify the human physiological response to digital facial expressions as conveyed in real-time by a humanoid robot.