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Dataset results
123 results for “Brain Computer Interface”
EEG Data for: "Composing only by thought: novel application of the P300 brain-computer interface"
<p>EEG Data for: "Composing only by thought: novel application of the P300 brain-computer interface". See the file "Information about the Dataset.pdf" for further information.</p>
Dataset used in "Steady state visual evoked potential (SSVEP) based brain-computer interface (BCI) performance under different perturbations" 2018, PLOS ONE
<p>This file contains the segmented EEG data in offline and online conditions. Please read the readme.doc file for the detailed explanation.</p>
Eight Reasons to Prioritize Brain-Computer Interface Cybersecurity
Open the record for dataset details and reuse information.
Beamforming in Noninvasive Brain–Computer Interfaces Dataset
<p>This is the dataset of 10 motor imagery subjects upon which the paper cited here is written. It is saved in the EEGLAB .set format with the digitized electrode positions included. The only issue is that the names for channels 65-128 are missing, and the head model that corresponds to these electrode locations is also poorly specified (see field Headmodel of the EEG struct). When using this data please cite:</p> <p>Grosse-Wentrup, Moritz, et al. "Beamforming in noninvasive brain–computer interfaces." <em>IEEE Transactions on Biomedical Engineering</em> 56.4 (2009): 1209-1219.</p> <p>DOI: <a href="https://doi.org/10.1109/TBME.2008.2009768">10.1109/TBME.2008.2009768</a></p>
Brain Invaders Adaptive versus Non-Adaptive P300 Brain-Computer Interface dataset
<p><strong>Summary:</strong></p> <p>This dataset contains electroencephalographic (EEG) recordings of 24 subjects doing a visual P300 Brain-Computer Interface experiment on PC. The visual P300 is an event-related potential elicited by visual stimulation, peaking 240-600 ms after stimulus onset. The experiment was designed in order to compare the use of a P300-based brain-computer interface on a PC with and without adaptive calibration using Riemannian geometry. The brain-computer interface is based on electroencephalography (EEG). EEG data were recorded thanks to 16 electrodes. A full description of the experiment is available at <a href="https://hal.archives-ouvertes.fr/hal-02103098">https://hal.archives-ouvertes.fr/hal-02103098</a>. Data were recorded during an experiment taking place in the GIPSA-lab, Grenoble, France, in 2013 (Congedo, 2013). Python code for manipulating the data is available at <a href="https://github.com/plcrodrigues/py.BI.EEG.2013-GIPSA">https://github.com/plcrodrigues/py.BI.EEG.2013-GIPSA</a>. The ID of this dataset is<em> BI.EEG.2013-GIPSA</em>.</p> <p> </p> <p><strong>Full description of the experiment and dataset:</strong> <a href="https://hal.archives-ouvertes.fr/hal-02103098">https://hal.archives-ouvertes.fr/hal-02103098</a></p> <p> </p> <p><strong><em>Principal Investigator</em>:</strong> B.Sc. Erwan Vaineau, Ph.D. Alexandre Barachant</p> <p> </p> <p><strong><em>Technical Supervisors</em>: </strong>Eng. Anton Andreev, Eng. Pedro. L. C. Rodrigues, Eng. Grégoire Cattan</p> <p> </p> <p><strong><em>Scientific Supervisor:</em></strong> Ph.D. Marco Congedo</p> <p> </p> <p><strong>ID of the dataset: </strong><em>BI.EEG.2013-GIPSA</em></p>
Effects of a Vibro-Tactile P300 Based Brain-Computer Interface on the Coma Recovery Scale-Revised in Patients With Disorders of Consciousness
<p>Persons diagnosed with disorders of consciousness (DOC) typically suffer from motor and cognitive disabilities. Recent research has shown that non-invasive brain-computer interface (BCI) technology could help assess these patients’ cognitive functions and command following abilities. 20 DOC patients participated in the study and performed 10 vibro-tactile P300 BCI sessions over 10 days with 8–12 runs each day. Vibrotactile tactors were placed on the each patient’s left and right wrists and one foot. Patients were instructed, via earbuds, to concentrate and silently count vibrotactile pulses on either their left or right wrist that presented a target stimulus and to ignore the others. Changes of the BCI classification accuracy were investigated over the 10 days. In addition, the Coma Recovery Scale-Revised (CRS-R) score was measured before and after the 10 vibro-tactile P300 sessions. In the first run, 10 patients had a classification accuracy above chance level (>12.5%). In the best run, every patient reached an accuracy ≥60%. The grand average accuracy in the first session for all patients was 40%. In the best session, the grand average accuracy was 88% and the median accuracy across all sessions was 21%. The CRS-R scores compared before and after 10 VT3 sessions for all 20 patients, are showing significant improvement (<em>p</em> = 0.024). Twelve of the twenty patients showed an improvement of 1 to 7 points in the CRS-R score after the VT3 BCI sessions (mean: 2.6). Six patients did not show a change of the CRS-R and two patients showed a decline in the score by 1 point. Every patient achieved at least 60% accuracy at least once, which indicates successful command following. This shows the importance of repeated measures when DOC patients are assessed. The improvement of the CRS-R score after the 10 VT3 sessions is an important issue for future experiments to test the possible therapeutic applications of vibro-tactile and related BCIs with a larger patient group.</p>
Data and software for "Mental Tasks for Controlling Cursor Movements in a Brain Computer Interface"
<p>All data for the experimental subjects on the examined mental tasks is contained in the "BCI_IFS_RECORDING_2012MARCH~APRIL_GroupIII" Zip folder.</p> <p>The software that was used to process the data is contained in the "IETE3.2_CROSS_VALID_AUTO" Zip folder.</p>
Non-Invasive Brain-Computer Interface Combined With Transcranial Electrical Stimulation for Peripheral Facial PalsyStimulation in the Treatment of Peripheral Facial Palsy
ClinicalTrials.gov study NCT07327710. IPD Sharing: NO. Countries: 1. Publications: 7.
A P300 Brain Computer Interface Keyboard to Control Assistive Technology For Use by People With Amyotrophic Lateral Sclerosis
ClinicalTrials.gov study NCT01119001. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Validation of a Brain-Computer Interface for Stroke Neurological Upper Limb Rehabilitation
ClinicalTrials.gov study NCT04724824. IPD Sharing: YES. Countries: 1. Publications: 2.
Stroke Rehabilitation Using Brain-Computer Interface (BCI) Technology
ClinicalTrials.gov study NCT04141774. IPD Sharing: NO. Countries: 1. Publications: 5.
Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface
Open the record for dataset details and reuse information.
Dataset of Easy screen P300 speller brain–computer interface design
<p><span>This study tested an application on 30 subjects, comprising 11 healthy women and 19 healthy men. Brain signals were recorded using a Brain Products V-Amp 16 Channel EEG system, with electrodes positioned according to the International 10-20 system. The signals were filtered using a 1-12 Hz Butterworth band-pass and a 50 Hz Notch filter, then digitized at a sampling frequency of 2 kHz and transferred to a computer for further analysis.</span></p>
DiSCIoser: Improving Arm Sensorimotor Functions After Spinal Cord Injury Via Brain-Computer Interface Training
ClinicalTrials.gov study NCT05637775. IPD Sharing: NO. Countries: 1. Publications: 5.
Brain-Computer Interface-based Programme for the Treatment of ASD/ADHD
ClinicalTrials.gov study NCT02618135. IPD Sharing: Not stated. Countries: 1. Publications: 8.
Brain Computer Interface（BCI） System for Stroke Rehabilitation
ClinicalTrials.gov study NCT02323061. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Sensorimotor Imaging for Brain-Computer Interfaces
ClinicalTrials.gov study NCT04723823. IPD Sharing: YES. Countries: 1. Publications: 0.
Assistive Soft Robotic Glove Intervention Using Brain-Computer Interface for Elderly Stroke Patients
ClinicalTrials.gov study NCT03277508. IPD Sharing: NO. Countries: 1. Publications: 9.
Effect of Brain-Computer Interfaced-Assisted Motor Imagery for Gait Retraining in Stroke Patients
ClinicalTrials.gov study NCT02507895. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Application of Mindfulness Meditation Based on Brain Computer Interface in Radiofrequency Ablation
ClinicalTrials.gov study NCT05306015. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.