xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
Ministerio de Economía y Competitividad (España)
Sponsor:
This work has been supported by the Spanish government’s projects ALCIT (TEC2012-38800-C03-01), AGES (S2010/BMD-2422), and OTOSiS (TEC2013-41718-R), and COMPREHENSION (TEC2012-38883-C02-01). D. Luengo has also been funded by the BBVA Foundation’s “I Convocatoria de Ayudas Fundación BBVA a Investigadores, Innovadores y Creadores Culturales”.
Project:
Gobierno de España. TEC2012-38800-C03-01/ALCIT Gobierno de España. S2010/BMD-2422/AGES Gobierno de España. TEC2013-41718-R/OTOSiS Gobierno de España. TEC2012-38883-C02-01/COMPREHENSION
Multi-channel intracardiac electrocardiograms (electrograms) are sequentially acquired during heart surgery performed on patients with sustained atrial fibrillation (AF) to guide radio frequency catheter ablation. These electrograms are used by cardiologists tMulti-channel intracardiac electrocardiograms (electrograms) are sequentially acquired during heart surgery performed on patients with sustained atrial fibrillation (AF) to guide radio frequency catheter ablation. These electrograms are used by cardiologists to determine candidate areas for ablation (e.g., areas corresponding to high dominant frequencies or complex electrograms). In this paper, we introduce a novel hierarchical causality analysis method for the multi-output sequentially acquired electrograms. The causal model obtained provides important information regarding delays among signals as well as the direction and strength of their causal connections. The tool developed may ultimately serve to guide cardiologists towards candidate areas for catheter ablation. Preliminary results on synthetic signals are used to validate the proposed approach.[+][-]
Description:
Proceeding of 2015 Computing in Cardiology Conference (CinC 2015), September 6-9, 2015, Nice, France