The past decade has witnessed the great success of deep neural networks in various
domains. However, deep neural networks are very resource-intensive in terms of energy …

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 …

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 …

Given the rapid development of brain–computer interfaces, emotion identification based on
EEG signals has emerged as a new study area with tremendous importance in recent years …

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 …

Nowadays, emotion recognition using electroencephalogram (EEG) signals is becoming a
hot research topic. The aim of this paper is to classify emotions of EEG signals using a novel …

Most of the current development of artificial intelligence is based on brain cognition,
however, this replication of biology cannot simulate the subjective emotional and mental …

A methodological contribution to a reproducible Measurement of Emotions for an EEG-
based system is proposed. Emotional Valence detection is the suggested use case. Valence …

A brain–computer interface (BCI) enables a user to communicate directly with a computer
using only the central nervous system. An affective BCI (aBCI) monitors and/or regulates the …

Electroencephalography (EEG)-based affective computing has a scarcity problem. As a
result, it is difficult to build effective, highly accurate and stable models using machine …