Microcanonical processing methodology for ECG and intracardial potential: application to atrial fibrillation

Oriol Pont (1) , Michel Haïssaguerre (2) , Hussein Yahia (1) , Nicolas Derval (3) , Mélèze Hocini (3)

1 GeoStat - Geometry and Statistics in acquisition data
2 Hôpital Haut-Lévêque
3 Département de cardiologie

Cardiac diseases are the principal cause of human morbidity and mortality in the western world. The electric potential of the heart is a highly complex signal emerging as a result of nontrivial flow conduction, hierarchical structuring and multiple regulation mechanisms. Its proper accurate analysis becomes of crucial importance in order to detect and treat arrhythmias or other abnormal dynamics that could lead to life-threatening conditions. To achieve this, advanced nonlinear processing methods are needed: one example here is the case of recent advances in the Microcanonical Multiscale Formalism. The aim of the present paper is to recapitulate those advances and extend the analyses performed, specially looking at the case of atrial fibrillation. We show that both ECG and intracardial potential signals can be described in a model-free way as a fast dynamics combined with a slow dynamics. Sharp differences in the key parameters of the fast dynamics appear in different regimes of transition between atrial fibrillation and healthy cases. Therefore, this type of analysis could be used for automated early warning, also in the treatment of atrial fibrillation particularly to guide radiofrequency ablation procedures.

Domaines: Mécanique statistique [cond-mat.stat-mech]; Physique Médicale [physics.med-ph]

Oriol Pont, Michel Haïssaguerre, Hussein Yahia, Nicolas Derval, Mélèze Hocini. Microcanonical processing methodology for ECG and intracardial potential: application to atrial fibrillation. Transactions on Mass-Data Analysis of Images and Signals, 2011, 3 (1), pp.15-34. ⟨hal-00690401⟩