Discover datasets

This dataset comprises EEG recordings from 10 healthy subjects performing a P300-based brain-computer interface task using a 9x8 character grid with face/house visual stimuli. The study is part of the BigP3BCI project, the largest public P300 BCI dataset, and includes single-session recordings with 32-channel EEG data sampled at 256 Hz. Data were collected for speller application development with online feedback in a laboratory setting.

Participants

10

HED

v8.4.0

Size

474 MB

Version

vv1.0.0

Updated

Jul 10, 2026

A multi-day motor imagery brain-computer interface (MI-BCI) dataset comprising EEG recordings from 51 healthy subjects performing left and right hand motor imagery tasks across three sessions. The dataset includes 59-channel EEG data (plus 1 ECG and 4 EOG channels) sampled at 1000 Hz with standardized 10-05 electrode montage, totaling 39,600 trials with visual and auditory cues. This resource supports the development and benchmarking of BCI algorithms for motor control applications.

Participants

51

Citations

29

HED

v8.4.0

Size

58.4 GB

Version

vv1.0.0

Updated

Jul 10, 2026

A motor imagery brain-computer interface dataset comprising EEG recordings from 52 healthy subjects performing kinesthetic imagery of left and right hand finger movements. The dataset includes 100-120 trials per class with concurrent EMG recordings, psychological and physiological questionnaires, 3D electrode coordinates, and non-task-related control states. Mean classification accuracy of 67.46% (±13.17%) demonstrates substantial performance variation across subjects, making it valuable for investigating subject-to-subject transfer in BCI applications.

Participants

52

Citations

92

HED

v8.4.0

Size

6.75 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalographic (EEG) recordings from 71 healthy subjects performing a visual P300-based brain-computer interface task using the Brain Invaders videogame. Participants engaged with an oddball paradigm involving pseudo-random flashes of 36 symbols on a grid to elicit P300 event-related potentials. The study evaluated the feasibility of a calibration-less P300 BCI system using 16 dry electrodes, with real-time adaptive classification for online feedback during gameplay. Subjects completed up to three game sessions.

Participants

64

Citations

18

HED

v8.4.0

Size

1.03 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG and EMG recordings from 15 healthy participants performing emergency braking tasks during simulated driving at 200 Hz sampling rate. Participants drove a virtual racing car following a computer-controlled lead vehicle, with occasional abrupt decelerations requiring immediate emergency braking responses. The study demonstrates the feasibility of predicting driver braking intentions from neural and muscular signals, with established applications in neuroergonomics and driver assistance systems. Currently 15 of 18 subjects are available.

Participants

15

Citations

81

HED

v8.4.0

Size

4.01 GB

Version

vv1.0.0

Updated

Jul 10, 2026

A 32-channel EEG dataset comprising visual imagery recordings from 22 healthy participants performing mental imagery tasks of 10 distinct categories (animals, geometric figures, and objects). The dataset contains 16,800 trials collected across 2 sessions per subject with simultaneous EEG acquisition at 1000 Hz, designed to support brain-computer interface research and classification algorithm development.

Participants

22

Citations

1

HED

v8.4.0

Size

31.7 GB

Version

vv1.0.0

Updated

Jul 10, 2026

A derivative EEG dataset comprising checkerboard m-sequence-based code-modulated visual evoked potentials (c-VEP) recordings from 16 healthy participants across 8 sessions. The dataset evaluates the influence of spatial frequency in visual stimuli for brain-computer interface applications, with 16-channel EEG data sampled at 256 Hz and annotated with HED 8.4.0 event labels for two stimulus intensity classes.

Participants

16

Citations

6

HED

v8.4.0

Size

622 MB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 16 healthy participants performing a code-modulated visual evoked potential (c-VEP) brain-computer interface task using p-ary m-sequences. The study evaluates non-binary m-sequence stimulation patterns to enhance user comfort in c-VEP-based BCIs. Data were collected across 5 sessions per subject with 8 runs per session at 256 Hz sampling rate using 16 EEG channels, providing a comprehensive resource for BCI research and algorithm development.

Participants

16

Citations

27

HED

v8.4.0

Size

764 MB

Version

vv1.0.0

Updated

Jul 10, 2026

A 7-day longitudinal motor imagery brain-computer interface (BCI) EEG dataset comprising 20 healthy participants performing four imagery tasks (left hand, right hand, both feet, and rest) across 7 sessions. The dataset contains 33,600 trials recorded at 500 Hz from 41 EEG channels using a Neuroscan SynAmps2 system with visual arrow cue stimulation. Data were preprocessed and annotated with HED 8.4.0 tags, supporting BCI research and algorithm development for motor imagery decoding.

Participants

20

Citations

14

HED

v8.4.0

Size

16.0 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalographic recordings from 21 healthy subjects performing a visual P300 experiment in two conditions: personal computer and virtual reality environments. The study compares P300-based brain-computer interface performance across these modalities using a 6×6 matrix speller paradigm with 16-channel EEG acquisition at 512 Hz. The dataset includes 12 experimental blocks per session with randomized session order and stimulus presentation to evaluate physiological responses, subjective experience, and BCI performance differences between PC and VR presentation.

Participants

21

Citations

5

HED

v8.4.0

Size

358 MB

Version

vv1.0.0

Updated

Jul 10, 2026