Discover datasets

A comprehensive EEG dataset comprising 54 healthy subjects performing three major brain-computer interface (BCI) paradigms—motor imagery, event-related potentials, and steady-state visually evoked potentials—across two sessions. The dataset investigates BCI illiteracy rates and performance variations, revealing that motor imagery exhibits the highest illiteracy rate (53.7%) compared to other paradigms, while all participants demonstrated proficiency with at least one BCI system.

Participants

23

Channels

62 (10-05)

Citations

98

HED

v8.4.0

Size

60.8 GB

Version

vv1.0.1

Updated

Jul 10, 2026

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.

Participants

54

Channels

62 (10-05)

Citations

100

HED

v8.4.0

Size

38.6 GB

Version

vv1.0.1

Updated

Jul 10, 2026

This open-access hybrid brain-computer interface dataset combines simultaneous EEG and near-infrared spectroscopy (NIRS) recordings from 29 healthy subjects performing mental arithmetic and motor imagery tasks. Experiment B focuses on mental arithmetic (serial subtraction) versus rest conditions across six sessions with 20 trials per session. The dataset includes preprocessed EEG data (30 channels, 200 Hz sampling rate) with comprehensive artifact correction and has been validated for single-trial classification using common spatial patterns and linear discriminant analysis.

Participants

29

Channels

30 (10-05)

Citations

94

HED

v8.4.0

Size

1.87 GB

Version

vv1.0.1

Updated

Jul 10, 2026

An open access hybrid brain-computer interface dataset combining electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings from 29 healthy subjects performing motor imagery and mental arithmetic tasks. The dataset includes preprocessed EEG data (30 channels, 200 Hz sampling rate) and NIRS data with validated classification performance demonstrating enhanced discrimination of mental states through multimodal analysis compared to single modality approaches.

Participants

29

Channels

30 (10-05)

Citations

94

HED

v8.4.0

Size

1.87 GB

Version

vv1.0.1

Updated

Jul 10, 2026

A P300-based brain-computer interface dataset comprising EEG recordings from 8 subjects (4 disabled, 4 able-bodied) performing a visual oddball task with image stimuli. The dataset includes 32-channel EEG data sampled at 2048 Hz from 4 sessions per subject, with 810 total trials per subject (135 targets, 675 non-targets) classified using Fisher's linear discriminant analysis and Bayesian linear discriminant analysis. This derivative dataset demonstrates high classification accuracy (100%) and information transfer rates suitable for BCI applications in disabled populations.

Participants

8

Citations

82

HED

v8.4.0

Size

1.94 GB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

37

Channels

32 (10-10)

HED

v8.4.0

Size

2.59 GB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

10

Channels

61 (10-05)

HED

v8.4.0

Size

1.20 GB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

30

Channels

32 (10-10)

HED

v8.4.0

Size

975 MB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

10

Channels

60 (10-10)

HED

v8.4.0

Size

1.60 GB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

10

Channels

128 (other)

HED

v8.4.0

Size

5.42 GB

Version

vv1.0.0

Updated

Jul 10, 2026