Emotion recognition from EEG signals is a major field of research in cognitive computing.
The major challenges involved in the task are extracting meaningful features from the …

Fusing multichannel neurophysiological signals to recognize human emotion states
becomes increasingly attractive. The conventional methods ignore the complementarity …

Emotion recognition based on electroencephalography (EEG) has received much attention
in recent years, and there is more and more research on emotion recognition utilizing deep …

Emotion recognition is a vital but challenging step in creating passive brain-computer
interface applications. In recent years, many studies on electroencephalogram (EEG)-based …

Emotion is an important factor that decides the the state of the mind of an individual.
However, there are many people who cannot express their emotions explicitly due to various …

Emotion analysis is the key technology in human–computer emotional interaction and has
gradually become a research hotspot in the field of artificial intelligence. The key problems …

This paper addresses the problem of EEG-based emotion recognition and classification and
investigates the performance of classifiers for subject-independent and subject-dependent …

In recent years, artificial intelligence (AI) technology has promoted the development of
electroencephalogram (EEG) emotion recognition. However, existing methods often …

Background: Emotion is a strong feeling such as love, anger, fear, etc. Emotion can be
recognized in two ways, ie, External expression and Biomedical data-based. Nowadays …

In recent years, graph convolutional neural networks have become research focus and
inspired new ideas for emotion recognition based on EEG. Deep learning has been widely …