DEAP — Database for Emotion Analysis using Physiological Signals
Citation: Koelstra, S., et al. (2012). IEEE Transactions on Affective Computing, 3(1), 18-31.
DOI: 10.1109/T-AFFC.2011.15
Access: eecs.qmul.ac.uk/mmv/datasets/deap/
Tier: 2
Overview
32 participants watched 40 one-minute music video clips. Self-reported valence, arousal, dominance, like/dislike.
Signals
- EEG (32 channels)
- GSR / EDA
- Plethysmograph (blood volume)
- Skin temperature
- Respiration
- EOG (eye movements)
- EMG (facial muscle activity)
Relevance
Widely used emotion benchmark. Arousal dimension can serve as proxy for pre-meltdown arousal state. GSR (EDA) + plethysmograph + temperature align with key Meltdown Minder signal types. Not wrist-worn but same physiological signals.