In this research, an emotion recognition system is developed based on valence/arousal
model using electroencephalography (EEG) signals. EEG signals are decomposed into the …

Emotion recognition in real-time using electroencephalography (EEG) signals play a key
role in human-computer interaction and affective computing. The existing emotion …

Emotion recognition from Electroencephalography (EEG) is proved to be a good choice as it
cannot be mimicked like speech signals or facial expressions. EEG signals of emotions are …

Introduction: The traditional machine learning-based emotion recognition models have
shown effective performance for classifying Electroencephalography (EEG) based emotions …

Emotion recognition based on electroencephalogram (EEG) signal is attracting more and
more attention. Many feature engineering based models have been investigated. However …

Emotion plays a nuclear part in human attention, decision-making, and communication.
Electroencephalogram (EEG)-based emotion recognition has developed a lot due to the …

Emotions are the most fundamental feature for non-verbal communication between human
and machine. To extract the original expectation of mind, emotion recognition and …

Emotion is the most important component in daily interaction between people. Nowadays, it
is important to make the computers understand user's emotion who interacts with it in human …

Emotion is a significant parameter in daily life and is considered an important factor for
human interactions. The human-machine interactions and their advanced stages like …

The objective of this paper is online recognition of human emotions based on
electroencephalogram (EEG) signals. The emotions are originated from the central and …