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BigP3BCI Study O is a P300-based brain-computer interface dataset comprising EEG recordings from 18 ALS subjects across 2 sessions each. Participants performed a visual speller task using a 9x8 character grid with supervised/checkerboard stimulus paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz, annotated with target and non-target event labels, and is part of the larger BigP3BCI collection representing one of the most comprehensive public P300 BCI datasets.

Size

981 MB

Updated

Jun 3, 2026

Participants

18

Participants

31

Participants

1

Participants

85

Participants

31

BigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects across 20 studies. The data were acquired at 256 Hz using 16-channel EEG with a standard 10-20 montage and are organized in BIDS format with HED event annotations for standardized analysis and machine learning applications.

Size

426 MB

Updated

Jun 3, 2026

Participants

1

This EEG dataset comprises recordings from 54 healthy participants performing a P300-based copy-spelling task using a 36-symbol row-column speller paradigm. The dataset includes 62 EEG channels and 4 EMG channels sampled at 1000 Hz, with offline training and online test phases designed to investigate BCI illiteracy. Data are provided in BIDS format with HED event annotations and represent a benchmark resource for evaluating brain-computer interface performance across different user populations.

Size

38.6 GB

Updated

Jun 3, 2026