Brain

Recent advances in scalp electroencephalography (EEG) as a neuroimaging tool have now allowed researchers to overcome technical challenges and movement restrictions typical in traditional neuroimaging studies.  Fortunately, recent mobile EEG devices have enabled studies involving cognition and motor control in natural environments that require mobility, such as during art perception and production in a museum setting, and during locomotion tasks.

1247 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Tue, 11/12/2019 - 10:38

    This dataset is associated with the paper, Jackson & Hall 2016, which is open source, and can be found here: http://ieeexplore.ieee.org/document/7742994/

    The DataPort Repository contains the data used primarily for generating Figure 1.

    687 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Sat, 06/16/2018 - 23:05

    Ten volunteers were trained through a series of twelve daily lessons to type in a computer using the Colemak keyboard layout. During the fourth-, eight-, and eleventh-session, electroencephalography (EEG) measurements were acquired for the five trials each subject performed in the corresponding lesson. Electrocardiography (ECG) data at each of those trials were acquired as well. The purpose of this experiment is to aim in the development of different methods to assess the process of learning a new task.

    320 views
  • Neuroscience
  • Last Updated On: 
    Thu, 06/25/2020 - 17:14

    EEG signals of various subjects in text files are uploaded. It can be useful for various EEG signal processing algorithms- filtering, linear prediction, abnormality detection, PCA, ICA etc.

    36 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 06/11/2020 - 06:45

     

    Participants were 61 children with ADHD and 60 healthy controls (boys and girls, ages 7-12). The ADHD children were diagnosed by an experienced psychiatrist to DSM-IV criteria, and have taken Ritalin for up to 6 months. None of the children in the control group had a history of psychiatric disorders, epilepsy, or any report of high-risk behaviors.

     

    547 views
  • Machine Learning
  • Last Updated On: 
    Mon, 06/15/2020 - 02:42

    This dataset has been collected in the Patient Recovery Center (a  24-hour,  7-day  nurse  staffed  facility)  with  medical  consultant   from  the  Mobile  Healthcare  Service of Hamad Medical Corporation.

    408 views
  • Artificial Intelligence
  • Last Updated On: 
    Thu, 04/30/2020 - 11:04

    Dataset asscociated with a paper to appear in IEEE Transactions on Pattern Analysis and Machine Intelligence

    "The perils and pitfalls of block design for EEG classification experiments"

    The paper has been accepted and is in production.

    We will upload the dataset when the paper is published.

    This is a placeholder so we can obtain a DOI to include in the paper.

    74 views
  • Artificial Intelligence
  • Last Updated On: 
    Fri, 04/24/2020 - 16:39

    BCI-Double-ErrP-Dataset is an EEG dataset recorded while participants used a P300-based BCI speller. This speller uses a P300 post-detection based on Error-related potentials (ErrPs) to detect and correct errors (i.e. when the detected symbol does not match the user’s intention). After the P300 detection, an automatic correction is made when an ErrP is detected (this is called a “Primary ErrP”). The correction proposed by the system is also evaluated, eventually eliciting a “Secondary ErrP” if the correction is wrong.

    200 views
  • Machine Learning
  • Last Updated On: 
    Fri, 03/20/2020 - 08:13

    Ear-EEG recording collects brain signals from electrodes placed in the ear canal. Compared with existing scalp-EEG,  ear-EEG is more wearable and user-comfortable compared with existing scalp-EEG.

    118 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Wed, 02/19/2020 - 03:24

    This dataset contains light-field microscopy images and converted sub-aperture images. 

     

    The folder with the name "Light-fieldMicroscopeData" contains raw light-field data. The file LFM_Calibrated_frame0-9.tif contains 9 frames of raw light-field microscopy images which has been calibrated. Each frame corresponds to a specific depth. The 9 frames cover a depth range from 0 um to 32 um with step size 4 um. Files with name LFM_Calibrated_frame?.png are the png version for each frame.

     

    135 views
  • Image Processing
  • Last Updated On: 
    Thu, 02/27/2020 - 10:07

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