• DocumentCode
    3684856
  • Title

    Real-time EEG Source-mapping Toolbox (REST): Online ICA and source localization

  • Author

    Luca Pion-Tonachini;Sheng-Hsiou Hsu;Scott Makeig;Tzyy-Ping Jung;Gert Cauwenberghs

  • Author_Institution
    Dept. of Electrical and Computer Engineering and Swartz Center for Computational Neuroscience, (SCCN) of University of California, San Diego (UCSD), USA
  • fYear
    2015
  • Firstpage
    4114
  • Lastpage
    4117
  • Abstract
    The Electroencephalogram (EEG) is a noninvasive functional brain activity recording method that shows promise for becoming a 3-D cortical imaging modality with high temporal resolution. Currently, most of the tools developed for EEG analysis focus mainly on offline processing. This study introduces and demonstrates the Real-time EEG Source-mapping Toolbox (REST), an extension to the widely distributed EEGLAB environment. REST allows blind source separation of EEG data in real-time using Online Recursive Independent Component Analysis (ORICA), plus near real-time localization of separated sources. Two source localization methods are available to fit equivalent current dipoles or estimate spatial source distributions of selected sources. Selected measures of raw EEG data or component activations (e.g. time series of the data, spectral changes over time, equivalent current dipoles, etc.) can be visualized in near real-time. Finally, this study demonstrates the accuracy and functionality of REST with data from two experiments and discusses some relevant applications.
  • Keywords
    "Electroencephalography","Scalp","Brain models","Real-time systems","Integrated circuits","Position measurement"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7319299
  • Filename
    7319299