Title :
Independence of complexity and of predictability detect nonlinear coupling of atrial activation processes during atrial fibrillation in humans
Author :
Censi, F. ; Barbaro, V. ; Bartolini, P. ; Calcagnini, G. ; Morelli, S. ; Michelucci, A. ; Cerutti, S.
Author_Institution :
Dept. of Inf. & Syst. Sci., Rome Univ., Italy
fDate :
6/21/1905 12:00:00 AM
Abstract :
Activation patterns underlying the electrical activity of the heart during Atrial Fibrillation (AF) are not entirely random. The aim of this study was to estimate the degree of coupling between two atrial sites by means of two indexes (Independence of Complexity and Independence of Predictability, IC and IF) based on a multivariate embedding procedure. We analyzed activation sequence of two atrial sites in 30 informed subjects during chronic AF of type I, II and III (Wells´ classification), 10 episodes each type, lasting 6 seconds. Surrogates were used to reject the hypothesis that the time series were generated by linear stochastic dynamics. In type I and II AF, IC and IP were significantly lower than their surrogates. In type III no coupling was detected IC and IP succeeded in detecting a nonlinear interaction between different atrial sites in type I and to a minor extent, type II AF
Keywords :
chaos; correlation methods; electrocardiography; entropy; medical signal processing; nonlinear dynamical systems; signal reconstruction; time series; Wells´ classification; activation sequence; atrial activation processes; atrial fibrillation; chaos; correlation integral; entropy; heart electrical activity; independence of complexity; independence of predictability; linear stochastic dynamics; multivariate embedding; nonlinear coupling; surrogate data; time series; Anatomy; Atrial fibrillation; Biomedical engineering; Cardiology; Catheters; Couplings; Heart; Humans; Stochastic processes; Surface waves;
Conference_Titel :
Computers in Cardiology, 1999
Conference_Location :
Hannover
Print_ISBN :
0-7803-5614-4
DOI :
10.1109/CIC.1999.825897
