Phase-Amplitude Coupling between EEG and EDA While Experiencing Multimedia Content

Abstract

Abstract-Emotion is a dynamic process that affects social relationships and influences the mechanisms of rational thinking and decision making. The influence of emotion on reasoning has gained a lot of attention in computer science. One approach to incorporating emotions into computers is by extracting features from various physiological signals and inferring the corresponding emotions or emotional dimensions. However, physiological processes are dynamic rather than static, and physiological signals mainly interact with each other during emotional processes rather than act individually. This study suggests that dynamical interdependencies of various signals that emanate from either the peripheral nervous system or the central nervous system might be involved in the emotional experience. Specifically, EEG (electroencephalography) signals captured from the temporal lobe are coupled with a narrow-band skin conductance response (SCR) while subjects are watching music clips, indicating that signals from the auditory cortex interact with SCR during this experience.

Spectators' Synchronization Detection based on Manifold Representation of Physiological Signals

“…In the field of affective computing, much research on emotion recognition in response to multimedia content has been carried out using EEG signals, peripheral physiological signals and facial expressions [9], [11]. In the area of highlights detection, various models have involved physiological measurements of a single viewer when watching of media, such as movies [7], music excerpts [14], and sport events [6].…”

Action Units and Their Cross-Correlations for Prediction of Cognitive Load during Driving

“…While constructing these features we were inspired by the Appraisal Model of Emotion, as proposed by Scherer [58], which states that the activation of certain physiological components are coupled, or synchronized, when we are faced with an emotional stimulus. Also following this theory, Kroupi et al have shown coupling between the phase and amplitude of the EEG and EDA signals while the subjects are watching emotionally stimulating music videos [59]. Another example of a similar analysis is the multiple works by Williamson et al, who have shown the existence of a difference in coordination, movement, and timing of vocal and facial components between patients suffering from major depressive disorder (MDD) vs. control subjects [60], [61], winning the AVEC 2013 [62] and AVEC 2014 [63] challenges on automatic detection of MDD severity.…”

Synchronization among Groups of Spectators for Highlight Detection in Movies

“…Since physiological reactions are considered to be an important component of emotions [15], [4], their measurements provide insight into spectators' aesthetic experience elicited by particular scenes [24]. In the field of affective computing, researchers have attempted to investigate emotion recognition in responses to multimedia content using electroencephalography (EEG) signals, peripheral physiological signals and facial expressions [14], [22]. The combination of spectators' physiological signals has been proposed in [5].…”