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Found 7 papers, 4 papers with code
Graph Neural Networks in EEG-based Emotion Recognition: A Survey
Besides, there is neither a comprehensive review nor guidance for constructing GNNs in EEG-based emotion recognition.
An EEG Channel Selection Framework for Driver Drowsiness Detection via Interpretability Guidance
However, the raw EEG data is inherently noisy and redundant, which is neglected by existing works that just use single-channel EEG data or full-head channel EEG data for model training, resulting in limited performance of driver drowsiness detection.
Interpretable and Robust AI in EEG Systems: A Survey
In this paper, we present the first comprehensive survey and summarize the interpretable and robust AI techniques for EEG systems.
Multi-View Spatial-Temporal Graph Convolutional Networks with Domain Generalization for Sleep Stage Classification
To address the above challenges, we propose a multi-view spatial-temporal graph convolutional networks (MSTGCN) with domain generalization for sleep stage classification.
HetEmotionNet: Two-Stream Heterogeneous Graph Recurrent Neural Network for Multi-modal Emotion Recognition
The research on human emotion under multimedia stimulation based on physiological signals is an emerging field, and important progress has been achieved for emotion recognition based on multi-modal signals.
SalientSleepNet: Multimodal Salient Wave Detection Network for Sleep Staging
Besides, the multimodal attention module is proposed to adaptively capture valuable information from multimodal data for the specific sleep stage.
GraphSleepNet: Adaptive Spatial-Temporal Graph Convolutional Networks for Sleep Stage Classification
However, how to effectively utilize brain spatial features and transition information among sleep stages continues to be challenging.
