• DocumentCode
    1678267
  • Title

    Principal component identification of variable single-trial evoked brain potentials

  • Author

    Lange, Daniel H. ; Inbar, Gideon F.

  • Author_Institution
    Technion City, Dept. of Electr. Eng., Haifa, Israel
  • fYear
    1996
  • Firstpage
    403
  • Lastpage
    405
  • Abstract
    Current single-trial evoked potential estimators assume deterministic signal waveforms embedded in the background electroencephalographic brain activity. Identification of morphological changes of the evoked responses has been suggested, requiring however a skilled operator to predetermine the location of the variable components. Here, the authors propose an alternative approach for the identification of variable single-trial evoked potentials, based on reconstruction of the single responses from the principal components of the data correlation matrix and thus eliminating the requirement of a-priori knowledge of the variable component locations. The reconstruction performance is demonstrated via simulations and application to experimental evoked potential data
  • Keywords
    electroencephalography; medical signal processing; a-priori knowledge; background electroencephalographic brain activity; data correlation matrix; deterministic signal waveforms; electrodiagnostics; experimental evoked potential data; morphological changes identification; principal component identification; reconstruction performance; variable single-trial evoked brain potentials; variable single-trial evoked potentials; Analytical models; Brain modeling; Cities and towns; Delay; Eigenvalues and eigenfunctions; Electroencephalography; Nominations and elections; Occupational safety; Performance analysis; Signal analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Electronics Engineers in Israel, 1996., Nineteenth Convention of
  • Conference_Location
    Jerusalem
  • Print_ISBN
    0-7803-3330-6
  • Type

    conf

  • DOI
    10.1109/EEIS.1996.567000
  • Filename
    567000