A Hybrid Deep Learning Architecture with Retrieval-Augmented Explanation Generation for Interpretable EEG-Based Stress Classification Across Multiple Paradigms
This paper presents a hybrid deep learning architecture integrating convolutional neural networks, bidirectional long short-term memory networks, self-attention, and retrieval-augmented generation (RAG) for accurate and interpretable electroencephalography (EEG)-based stress detection. The compact EEG encoder contains...