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, the rapid advances in machine learning (ML) and information fusion has
made it possible to endow machines/computers with the ability of emotion understanding …

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 …

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 …

High quality and efficient medical service is one of the major factors defining living
standards. Developed countries strive to make their healthcare systems as efficient and cost …

Recent technological advancements in data acquisition tools allowed life scientists to
acquire multimodal data from different biological application domains. Categorized in three …

Deep learning has emerged as a powerful machine learning technique that learns multiple
layers of representations or features of the data and produces state‐of‐the‐art prediction …

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

Rapid advances in hardware-based technologies during the past decades have opened up
new possibilities for life scientists to gather multimodal data in various application domains …

The electroencephalogram (EEG) is the most prominent means to study epilepsy and
capture changes in electrical brain activity that could declare an imminent seizure. In this …