title: A Multi-Variate Predictability Framework to Assess Invasive Cardiac Activity and Interactions During Atrial Fibrillation.
abstract: This study introduces a predictability framework based on the concept of Granger causality (GC), in order to analyze the activity and interactions between different intracardiac sites during atrial fibrillation (AF).
  
  
  
  GC-based interactions were studied using a three-electrode analysis scheme with multi-variate autoregressive models of the involved preprocessed intracardiac signals. The method was evaluated in different scenarios covering simulations of complex atrial activity as well as endocardial signals acquired from patients.
  
  
  
  The results illustrate the ability of the method to determine atrial rhythm complexity and to track and map propagation during AF.
  
  
  
  The proposed framework provides information on the underlying activation and regularity, does not require activation detection or postprocessing algorithms and is applicable for the analysis of any multielectrode catheter.
  
  
  
  The proposed framework can potentially help to guide catheter ablation interventions of AF.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Alcaine
authors.forename: Michela
authors.initials: M
authors.lastname: Mase
authors.forename: Alessandro
authors.initials: A
authors.lastname: Cristoforetti
authors.forename: Flavia
authors.initials: F
authors.lastname: Ravelli
authors.forename: Giandomenico
authors.initials: G
authors.lastname: Nollo
authors.forename: Pablo
authors.initials: P
authors.lastname: Laguna
authors.forename: Juan Pablo
authors.initials: JP
authors.lastname: Martinez
authors.forename: Luca
authors.initials: L
authors.lastname: Faes
mesh_terms: D001281:Atrial Fibrillation / Q000175:diagnosis / Q000503:physiopathology*; D018780:Body Surface Potential Mapping / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006329:Heart Conduction System / Q000503:physiopathology*; D006801:Humans; D008955:Models, Cardiovascular; D015233:Models, Statistical; D015999:Multivariate Analysis