nm000112
FACED - Finer-grained Affective Computing EEG Dataset
EEG Zarr
The Finer-grained Affective Computing EEG Dataset (FACED) contains 32-channel scalp EEG from 123 healthy participants who watched 28 emotion-eliciting video clips targeting nine emotion categories (four negative, four positive, and neutral). Participants gave self-reported ratings on 12 dimensions, including discrete emotions, valence, arousal, liking, and familiarity. The dataset supports cross-subject affective computing and the development of EEG-based emotion recognition algorithms. This version is converted to BIDS with events annotated by video and emotion labels.
- Participants
- 123
- Channels
- 32 (10-10)
- Citations
- 94
- Size
- 31.4 GB
- Version
- v1.1.3
- Updated
- May 29, 2026