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 …

Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …

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 …

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

Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not …

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 …

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 …

In this paper, we present a multimodal emotion recognition framework called EmotionMeter
that combines brain waves and eye movements. To increase the feasibility and wearability …

Emotion recognition based on electroencephalography (EEG) is of great important in the
field of Human–Computer Interaction (HCI), which has received extensive attention in recent …

Abstract Emotion recognition using Artificial Intelligence (AI) is a fundamental prerequisite to
improve Human-Computer Interaction (HCI). Recognizing emotion from …