Emotions are fundamental for human beings and play an important role in human cognition.
Emotion is commonly associated with logical decision making, perception, human …

This paper review the classification method of EEG signal based on k-nearest neighbor
(kNN) and support vector machine (SVM) algorithm. For instance, a classifier learns an input …

Emotion is interpreted as a psycho-physiological process, and it is associated with
personality, behavior, motivation, and character of a person. The objective of affective …

Emotion recognition is a crucial application in human–computer interaction. It is usually
conducted using facial expressions as the main modality, which might not be reliable. In this …

Multichannel electroencephalogram (EEG) is an array signal that represents brain neural
networks and can be applied to characterize information propagation patterns for different …

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 …

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 …

Much attention has been paid to the recognition of human emotions with the help of
electroencephalogram (EEG) signals based on machine learning technology. Recognizing …

As the most direct way to measure the true emotional states of humans, EEG-based emotion
recognition has been widely used in affective computing applications. In this paper, we aim …

The automated recognition of human emotions plays an important role in developing
machines with emotional intelligence. Major research efforts are dedicated to the …