Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Emotion recognition technology through analyzing the EEG signal is currently an essential
concept in Artificial Intelligence and holds great potential in emotional health care, human …

Previous electroencephalogram (EEG) emotion recognition relies on single-task learning,
which may lead to overfitting and learned emotion features lacking generalization. In this …

Affecting computing is an artificial intelligence area of study that recognizes, interprets,
processes, and simulates human affects. The user's emotional states can be sensed through …

Most previous EEG-based emotion recognition methods studied hand-crafted EEG features
extracted from different electrodes. In this article, we study the relation among different EEG …

The dynamic uncertain relationship among each brain region is a necessary factor that limits
EEG-based emotion recognition. It is a thought-provoking problem to availably employ time …

Current research suggests that there exist certain limitations in EEG emotion recognition,
including redundant and meaningless time-frames and channels, as well as inter-and intra …

Neuroscience study has revealed the discrepancy of emotion expression between the left
and right hemispheres of human brain. Inspired by this study, in this article, we propose a …

In this paper, we propose a novel Electroencephalograph (EEG) emotion recognition
method inspired by neuroscience with respect to the brain response to different emotions …

Since electroencephalogram (EEG) signals can truly reflect human emotional state, emotion
recognition based on EEG has turned into a critical branch in the field of artificial …