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 …

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 …

Emotion recognition from EEG signals is a major field of research in cognitive computing.
The major challenges involved in the task are extracting meaningful features from the …

The electroencephalogram (EEG) has great attraction in emotion recognition studies due to
its resistance to deceptive actions of humans. This is one of the most significant advantages …

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

Fusing multichannel neurophysiological signals to recognize human emotion states
becomes increasingly attractive. The conventional methods ignore the complementarity …

Electroencephalogram (EEG) based emotional analysis has been employed in medical
science, security and human–computer interaction with good success. In the recent past …

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 …

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

Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …