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EmoEEG-MC: A Multi-Context Emotional EEG Dataset for Cross-Context Emotion Decoding
EmoEEG-MC is a multi-context emotional EEG dataset comprising 64-channel EEG and peripheral physiological recordings (PPG, GSR) from 60 participants exposed to video-induced and imagery-induced emotional stimuli. Seven emotion categories (joy, inspiration, tenderness, fear, disgust, sadness, neutral) were evoked and validated through subjective reports, enabling investigation of cross-context emotion decoding. The dataset supports research on neural mechanisms of emotion and generalization of affective computing models across contexts.
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Coming soon. Per-file data-quality summaries are precomputed by the NEMAR processing pipeline. The static aggregate is on the way — tracked at nemar-cli#511.