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 …
Emotion-driven analysis and control of human-robot interactions in collaborative applications
The utilization of robotic systems has been increasing in the last decade. This increase has
been derived by the evolvement in the computational capabilities, communication systems …
been derived by the evolvement in the computational capabilities, communication systems …
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 …
Automated emotion recognition based on higher order statistics and deep learning algorithm
The objective of this paper is online recognition of human emotions based on
electroencephalogram (EEG) signals. The emotions are originated from the central and …
electroencephalogram (EEG) signals. The emotions are originated from the central and …
EEG-based emotion classification using spiking neural networks
Y Luo, Q Fu, J Xie, Y Qin, G Wu, J Liu, F Jiang… - IEEE …, 2020 - ieeexplore.ieee.org
A novel method of using the spiking neural networks (SNNs) and the electroencephalograph
(EEG) processing techniques to recognize emotion states is proposed in this paper. Three …
(EEG) processing techniques to recognize emotion states is proposed in this paper. Three …
Electroencephalography based fusion two-dimensional (2D)-convolution neural networks (CNN) model for emotion recognition system
The purpose of this study is to improve human emotional classification accuracy using a
convolution neural networks (CNN) model and to suggest an overall method to classify …
convolution neural networks (CNN) model and to suggest an overall method to classify …
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 …
Real-time fractal-based valence level recognition from EEG
Y Liu, O Sourina - Transactions on computational science XVIII: special …, 2013 - Springer
Emotions are important in human-computer interaction. Emotions could be classified based
on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of …
on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of …
The brain's response to pleasant touch: An EEG investigation of tactile caressing
Somatosensation as a proximal sense can have a strong impact on our attitude toward
physical objects and other human beings. However, relatively little is known about how …
physical objects and other human beings. However, relatively little is known about how …