• DocumentCode
    1790581
  • Title

    A tutorial on empirical mode decomposition in brain research

  • Author

    Cheolsoo Park

  • Author_Institution
    Dept. of Comput. Eng., Kwangwoon Univ., Seoul, South Korea
  • fYear
    2014
  • fDate
    22-25 June 2014
  • Firstpage
    1
  • Lastpage
    2
  • Abstract
    Brain electrical activity is often recorded via electroencephalogram (EEG) since it can be monitored using noninvasive and affordable recording equipment. When it comes to the analysis of EEG, there is a lack of signal processing technique to deal with the nonstationarity and nonlinearity of EEG signals. Here we present the data-driven algorithm, empirical mode decomposition suitable for the analysis of EEG.
  • Keywords
    bioelectric phenomena; electroencephalography; medical signal processing; EEG signal analysis; brain electrical activity; data-driven algorithm; electroencephalogram; empirical mode decomposition; signal processing technique; Algorithm design and analysis; Correlation; Electroencephalography; Empirical mode decomposition; Frequency modulation; Signal processing algorithms; Wavelet transforms; EEG; MEMD; empirical mode decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics (ISCE 2014), The 18th IEEE International Symposium on
  • Conference_Location
    JeJu Island
  • Type

    conf

  • DOI
    10.1109/ISCE.2014.6884517
  • Filename
    6884517
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1790581