• DocumentCode
    1657610
  • Title

    Principal components analysis for quantifying the anaesthetic effects on atrial fibrillation organization

  • Author

    Cervigón, R. ; Sánchez, C. ; Moreno, J. ; Millet, J. ; Castells, F.

  • Author_Institution
    GIBI, Univ. de Castilla La Mancha, Cuenca, Spain
  • fYear
    2009
  • Firstpage
    137
  • Lastpage
    140
  • Abstract
    Atrial fibrillation (AF) mechanisms are not completely understood yet. We evaluated the effect of the most useful anaesthetic agent in AF dynamics. Principal component analysis (PCA) has been applied as a method to analyze the variation between the different atrial signals extracted from electrogram. The purpose of PCA as a data decomposition procedure is to study the eigenvalues distribution along both atria during basal and anaesthetic states. The results suggest that in the right atrium exist differences between both states, with lower variability during the anaesthetic infusion.
  • Keywords
    eigenvalues and eigenfunctions; electrocardiography; principal component analysis; anaesthetic effects; atrial fibrillation organization; data decomposition; eigenvalues distribution; electrogram; principal components analysis; Atrial fibrillation; Catheters; Covariance matrix; Data mining; Electrodes; Matrix decomposition; Personal communication networks; Principal component analysis; Propagation delay; Signal processing; Atrial fibrillation; anaesthetic effect; principal component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
  • Conference_Location
    Cardiff
  • Print_ISBN
    978-1-4244-2709-3
  • Electronic_ISBN
    978-1-4244-2711-6
  • Type

    conf

  • DOI
    10.1109/SSP.2009.5278619
  • Filename
    5278619