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
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;
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
DOI :
10.1109/SSP.2009.5278619
