Automatic emotion recognition is one of the most challenging tasks. To detect emotion from
nonstationary EEG signals, a sophisticated learning algorithm that can represent high‐level …

Recent advancements in human-computer interaction research have led to the possibility of
emotional communication via brain-computer interface systems for patients with …

With the rapid development of Human-computer interaction, automatic emotion recognition
based on multichannel electroencephalography (EEG) signals has attracted much attention …

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 …

Understanding the expression of human emotional states plays a prominent role in
interactive multimodal interfaces, affective computing, and the healthcare sector. Emotion …

The existed methods for electroencephalograph (EEG) emotion recognition always train the
models based on all the EEG samples indistinguishably. However, some of the source …

Recently, electroencephalogram-based emotion recognition has become crucial in enabling
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …

Emotion recognition has attracted attention in recent years. It is widely used in healthcare,
teaching, human-computer interaction, and other fields. Human emotional features are often …

An adaptive neural decision tree is investigated to recognize electroencephalogram (EEG)
emotion signal with ability of intelligently selecting network structure. Firstly, to overcome …

A novel method of using the spiking neural networks (SNNs) and the electroencephalograph
(EEG) processing techniques to recognize emotion states is proposed in this paper. Three …