A systematic literature review of emotion recognition using EEG signals
In this study, we conducted a systematic literature review of 107 primary studies conducted
between 2017 and 2023 to discern trends in datasets, classifiers, and contributions to …
between 2017 and 2023 to discern trends in datasets, classifiers, and contributions to …
A review on semi-supervised learning for EEG-based emotion recognition
Semisupervised learning holds significant academic and practical importance in the realm of
EEG-based emotion recognition. Currently, a multitude of research endeavors are dedicated …
EEG-based emotion recognition. Currently, a multitude of research endeavors are dedicated …
Cross-cultural emotion recognition with EEG and eye movement signals based on multiple stacked broad learning system
With increasing social globalization, interaction between people from different cultures has
become more frequent. However, there are significant differences in the expression and …
become more frequent. However, there are significant differences in the expression and …
EEG-based emotion recognition for hearing impaired and normal individuals with residual feature pyramids network based on time–frequency–spatial features
F Hou, J Liu, Z Bai, Z Yang, J Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the development of affective computing, discriminative feature selection is critical for
electroencephalography (EEG) emotion recognition. In this article, we fused four EEG …
electroencephalography (EEG) emotion recognition. In this article, we fused four EEG …
Cross-subject EEG-based emotion recognition via semi-supervised multi-source joint distribution adaptation
M Jiménez-Guarneros… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Most emotion recognition systems still present limited applicability to new users due to the
intersubject variability of electroencephalogram (EEG) signals. Although domain adaptation …
intersubject variability of electroencephalogram (EEG) signals. Although domain adaptation …
Semi-supervised domain-adaptive seizure prediction via feature alignment and consistency regularization
The interpatient variability still poses a great challenge for the real-world application of
electroencephalogram (EEG)-based seizure prediction, where most previous methods could …
electroencephalogram (EEG)-based seizure prediction, where most previous methods could …
PR-PL: A novel prototypical representation based pairwise learning framework for emotion recognition using EEG signals
Affective brain-computer interface based on electroencephalography (EEG) is an important
branch in the field of affective computing. However, the individual differences in EEG …
branch in the field of affective computing. However, the individual differences in EEG …
Interpretable and robust ai in eeg systems: A survey
The close coupling of artificial intelligence (AI) and electroencephalography (EEG) has
substantially advanced human-computer interaction (HCI) technologies in the AI era …
substantially advanced human-computer interaction (HCI) technologies in the AI era …
Cross-subject EEG emotion recognition using multi-source domain manifold feature selection
Recent researches on emotion recognition suggests that domain adaptation, a form of
transfer learning, has the capability to solve the cross-subject problem in Affective brain …
transfer learning, has the capability to solve the cross-subject problem in Affective brain …
Functional connectivity-enhanced feature-grouped attention network for cross-subject EEG emotion recognition
W Guo, Y Li, M Liu, R Ma, Y Wang - Knowledge-Based Systems, 2024 - Elsevier
Electroencephalogram (EEG)-based automatic emotion recognition technologies are
gaining significant attention and have become crucial in the field of brain–computer …
gaining significant attention and have become crucial in the field of brain–computer …