A CNN-LSTM-attention model applied to DEAP EEG data, relabeled by an arousal threshold, is reported to detect stress with 81.25% accuracy and AUC 0.68, though the paper's own table reports 63% overall accuracy.
Scientific Reports14(1), 1234–1245 (2024)
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Brain2Vec: A Deep Learning Framework for EEG-Based Stress Detection Using CNN-LSTM-Attention
A CNN-LSTM-attention model applied to DEAP EEG data, relabeled by an arousal threshold, is reported to detect stress with 81.25% accuracy and AUC 0.68, though the paper's own table reports 63% overall accuracy.