Of late, emotion detection from brain signal has become a topic of research. Various
machine learning algorithms have been applied to classify the emotion as a psychological …

Throughout the years, major advancements have been made in the field of EEG-based
emotion classification. Implementing deep architectures for supervised and unsupervised …

Electroencephalogram (EEG) signal based automatic emotion recognition is an inter-
disciplinary field which has been studied for a long time. In this study, empirical mode …

Emotion can be defined as a voluntary or involuntary reaction to external factors. People
express their emotions through actions, such as words, sounds, facial expressions, and …

Automated assessment of human emotions via physiological signals has gained remarkable
significance in the development of affective human–machine interfaces for stress detection …

Emotion recognition based on brain-computer interface (BCI) has attracted important
research attention despite its difficulty. It plays a vital role in human cognition and helps in …

To achieve a highly efficient brain-computer interface (BCI) system regarding emotion
recognition from electroencephalogram (EEG) signal, the most crucial issues are feature …

Emotions have a vital role in the day-to-day life of human beings, the need and importance
of emotion recognition systems have increased with the role of human computer interface …

Emotion identification is an essential task for human–computer interaction systems.
Electroencephalogram (EEG) signals have been widely used in emotion recognition. So far …

Many scientific studies have been concerned with building an automatic system to recognize
emotions, and building such systems usually relies on brain signals. These studies have …