Evolutionary computation algorithms for feature selection of EEG-based emotion recognition using mobile sensors
There is currently no standard or widely accepted subset of features to effectively classify
different emotions based on electroencephalogram (EEG) signals. While combining all …
different emotions based on electroencephalogram (EEG) signals. While combining all …
Multimodal fusion framework: A multiresolution approach for emotion classification and recognition from physiological signals
The purpose of this paper is twofold:(i) to investigate the emotion representation models and
find out the possibility of a model with minimum number of continuous dimensions and (ii) to …
find out the possibility of a model with minimum number of continuous dimensions and (ii) to …
EEG channel correlation based model for emotion recognition
Abstract Emotion recognition using Artificial Intelligence (AI) is a fundamental prerequisite to
improve Human-Computer Interaction (HCI). Recognizing emotion from …
improve Human-Computer Interaction (HCI). Recognizing emotion from …
Emotions recognition using EEG signals: A survey
SM Alarcao, MJ Fonseca - IEEE transactions on affective …, 2017 - ieeexplore.ieee.org
Emotions have an important role in daily life, not only in human interaction, but also in
decision-making processes, and in the perception of the world around us. Due to the recent …
decision-making processes, and in the perception of the world around us. Due to the recent …
Emotion recognition from EEG signal focusing on deep learning and shallow learning techniques
Recently, electroencephalogram-based emotion recognition has become crucial in enabling
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
the Human-Computer Interaction (HCI) system to become more intelligent. Due to the …
Feature extraction and selection for emotion recognition from EEG
Emotion recognition from EEG signals allows the direct assessment of the “inner” state of a
user, which is considered an important factor in human-machine-interaction. Many methods …
user, which is considered an important factor in human-machine-interaction. Many methods …
Comparison of different feature extraction methods for EEG-based emotion recognition
EEG-based emotion recognition is a challenging and active research area in affective
computing. We used three-dimensional (arousal, valence and dominance) model of emotion …
computing. We used three-dimensional (arousal, valence and dominance) model of emotion …
A comparative analysis of machine learning methods for emotion recognition using EEG and peripheral physiological signals
V Doma, M Pirouz - Journal of Big Data, 2020 - Springer
Emotion recognition using brain signals has the potential to change the way we identify and
treat some health conditions. Difficulties and limitations may arise in general emotion …
treat some health conditions. Difficulties and limitations may arise in general emotion …
[HTML][HTML] A systematic review on automated human emotion recognition using electroencephalogram signals and artificial intelligence
Abstract Brain-Computer Interaction (BCI) system intelligence has become more dependent
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
Human emotion recognition with electroencephalographic multidimensional features by hybrid deep neural networks
Featured Application The method presented in this study can be applied in many fields, such
as mental health care, entertainment consumption behavior, society safety, and so on. For …
as mental health care, entertainment consumption behavior, society safety, and so on. For …