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

Affective computing, a subcategory of artificial intelligence, detects, processes, interprets,
and mimics human emotions. Thanks to the continued advancement of portable non …

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 …

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 …

Emotions are fundamental for human beings and play an important role in human cognition.
Emotion is commonly associated with logical decision making, perception, human …

Emotion recognition based on electroencephalography (EEG) is a significant task in the
brain-computer interface field. Recently, many deep learning-based emotion recognition …

Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …

Electroencephalography (EEG) measures the neuronal activities in different brain regions
via electrodes. Many existing studies on EEG-based emotion recognition do not fully exploit …

In this paper, a multichannel EEG emotion recognition method based on a novel dynamical
graph convolutional neural networks (DGCNN) is proposed. The basic idea of the proposed …

Assessment of the cognitive functions and state of clinical subjects is an important aspect of
e-health care delivery, and in the development of novel human-machine interfaces. A …