DocumentCode :
3595052
Title :
Characterizing complexity of atrial arrhythmias through effective dynamics from electric potential measures
Author :
Pont, O. ; Binbin Xu
Author_Institution :
GeoStat team, INRIA Bordeaux Sud-Ouest, Talence, France
fYear :
2013
Firstpage :
487
Lastpage :
490
Abstract :
The cardiac electrical activity follows a complex dynamics whose accurate description is crucial to characterize arrhythmias and classify their complexity. Rhythm reflects the connection topology of pacemaker cells at their source. Hence, characterizing the attractors as nonlinear, effective dynamics can capture the key parameters without imposing any particular model on the empirical signals. A dynamic phase-space reconstruction from appropriate embedding can be made robust and numerically stable with the presented method.
Keywords :
bioelectric potentials; blood vessels; cardiovascular system; cellular biophysics; electrocardiography; medical disorders; medical signal processing; nonlinear dynamical systems; pacemakers; signal classification; signal reconstruction; appropriate embedding; arrhythmia characterization; atrial arrhythmias; attractor characterization; cardiac electrical activity; complexity characterization; complexity classification; connection topology; dynamic phase-space reconstruction; effective dynamics; electric potential measurement; empirical signals; nonlinear dynamics; pacemaker cells; particular model; Abstracts; Adaptation models; Correlation; Fractals; Spirals;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing in Cardiology Conference (CinC), 2013
ISSN :
2325-8861
Print_ISBN :
978-1-4799-0884-4
Type :
conf
Filename :
6713420
Link To Document :
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