Discover datasets

Showing 10 of 764 datasets · page 63 of 77

nm000272
Romani et al. 2025 — BrainForm: a Serious Game for BCI Training and Data Collection (P300 ERP, University of Trento)

EEG

This dataset comprises scalp EEG recordings from 22 participants who used BrainForm, a gamified brain-computer interface (BCI) designed for P300 event-related potential (ERP) training and scalable data collection with consumer hardware. Participants performed repeated runs of a P300 spelling/selection task, allowing analysis of BCI skill acquisition across sessions and the effects of different visual stimulation textures on performance. The dataset supports research on BCI training, human factors, and machine learning applications on ERP data.

Participants

22

Channels

8 (10-10)

Citations

1

HED

v8.4.0

Size

237 MB

Version

v1.0.6

Updated

Aug 20, 2026

by Michele Romani et al.
nm000271
Chang et al. 2025 — A multi-paradigm EEG dataset for studying upper limb rehabilitation exercises (Lanzhou Jiaotong University)

EEG

This dataset contains scalp EEG recordings from 28 participants performing or imagining upper-limb rehabilitation exercises under a multi-paradigm protocol. It was designed to support research on motor-imagery-based brain–computer interfaces (BCI) for upper-limb rehabilitation. The data have been converted to BIDS format from the original dataset published by Chang et al. (2025).

Participants

28

Channels

59 (10-10)

Citations

3

HED

v8.4.0

Size

47.1 GB

Version

v1.0.5

Updated

Aug 20, 2026

by Wenwen Chang et al.
nm000270
Liu et al. 2025 — Lower limb motor imagery EEG dataset based on the multi-paradigm and longitudinal-training of stroke patients (Tianjin University)

EEG

This dataset comprises scalp EEG recordings from 27 stroke patients performing a lower-limb motor imagery task as part of a multi-paradigm, longitudinal rehabilitation training protocol. Data were collected at Tianjin University to support research on motor-imagery brain-computer interfaces for gait and lower-limb rehabilitation after stroke. The dataset is organized in BIDS format with a single EEG task (task-imagery) across repeated sessions.

Participants

27

Channels

64 (10-10)

Citations

23

HED

v8.4.0

Size

56.7 GB

Version

v1.0.5

Updated

Aug 20, 2026

by Yuan Liu et al.
nm000268
Shin et al. 2017 (Experiment B) — Open Access Dataset for EEG+NIRS Single-Trial Classification

EEG

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 preprocessed data at 200 Hz sampling rate. The dataset includes comprehensive preprocessing (bandpass filtering, ICA-based artifact rejection, common average referencing) and serves as a benchmark for validating hybrid BCI approaches that integrate multimodal neuroimaging signals.

Participants

29

Channels

30 (10-05)

Citations

94

HED

v8.4.0

Size

6.62 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Jaeyoung Shin et al.
nm000267
Shin et al. 2017 (Experiment A) — Open Access Dataset for EEG+NIRS Single-Trial Classification

EEG

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 EEG channels plus 2 EOG channels, 200 Hz sampling rate) and NIRS measurements (36 channels) across six sessions per subject, 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

6.50 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Jaeyoung Shin et al.
nm000266
Sosulski et al. 2019 — Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints

EEG

An auditory event-related potential dataset from 13 healthy subjects performing an oddball paradigm with two sinusoidal tones (target 1000 Hz, non-target 500 Hz) presented at variable stimulus onset asynchronies (60-600 ms). The dataset comprises 31-channel EEG recordings at 1000 Hz acquired with BrainProducts BrainAmp DC during an online closed-loop brain-computer interface experiment designed to optimize stimulation parameters using Bayesian optimization and random search strategies.

Participants

13

Channels

31 (10-10)

Citations

2

HED

v8.4.0

Size

3.68 GB

Version

v1.0.4

Updated

Aug 18, 2026

by Jan Sosulski et al.
nm000265
Guttmann-Flury et al. 2025 (Motor Imagery) — Dataset combining EEG, eye-tracking, and high-speed video for ocular activity analysis across BCI paradigms

EEG

A multimodal neuroimaging dataset combining EEG, eye-tracking, and high-speed video recordings from 31 healthy participants performing motor imagery tasks. The dataset comprises 2,520 trials across 63 sessions, with participants performing left and right hand motor imagery in response to visual cues. Recorded at 1000 Hz using a 64-channel EEG montage with standardized electrode placement, this dataset supports brain-computer interface research and analysis of ocular activity patterns during motor imagery paradigms.

Participants

31

Channels

62 (10-10)

Citations

11

HED

v8.4.0

Size

33.6 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Eva Guttmann-Flury et al.
nm000264
Vaineau, Barachant & Andreev 2013 — Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset (BI2013a)

EEG

This dataset comprises electroencephalographic recordings from 24 healthy subjects performing a visual P300 brain-computer interface task based on the Brain Invaders video game. The study compares adaptive versus non-adaptive calibration approaches using Riemannian geometry for classifier training. EEG data were acquired using 16 electrodes at 512 Hz sampling rate during sessions conducted at GIPSA-lab, Grenoble, France in 2013.

Participants

24

Channels

16 (10-10)

Citations

6

HED

v8.4.0

Size

3.00 GB

Version

v1.0.4

Updated

Aug 18, 2026

by E. Vaineau et al.
nm000260
Van Veen, Barachant & Andreev 2012 — Building Brain Invaders: EEG data of an experimental validation (BI2012)

EEG

This dataset comprises electroencephalographic recordings from 25 healthy subjects performing a visual P300 brain-computer interface task based on the Brain Invaders paradigm, a game inspired by Space Invaders. The experiment involved 16-channel EEG recordings at 128 Hz sampling rate during both training and online sessions with visual stimulus presentations. The dataset includes 128 target trials and 640 non-target trials per subject, with event-related potentials peaking 240-600 ms after stimulus onset.

Participants

23

Channels

17 (10-20)

Citations

3

HED

v8.4.0

Size

312 MB

Version

v1.0.4

Updated

Aug 18, 2026

by G.F.P. Van Veen et al.
nm000259
Speier et al. 2017 — A comparison of stimulus types in online classification of the P300 speller using language models

EEG

This dataset contains EEG recordings from 10 healthy adults performing a P300 speller task using a 6x6 character matrix, under two stimulus conditions (Famous Faces overlay and Inverting). Data were collected across two sessions per subject with three runs each, using a 32-channel g.tec EEG system at 256 Hz. The dataset is a BIDS-formatted derivative generated via MOABB from the original data reported in Speier et al. (2017), which compared classification approaches for the P300 speller using language models.

Participants

10

Channels

32 (10-10)

Citations

28

HED

v8.4.0

Size

773 MB

Version

v1.0.4

Updated

Aug 20, 2026

by William Speier et al.