ICA APPLIED TO ATRIAL FIBRILLATION ANALYSIS
José Joaquín Rieta, Francisco Castells, César Sánchez, Jorge Igual · 2003
In this work we present a new biomedical application of independent component analysis (ICA) to solve the problem of atrial activity (AA) extraction from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). The proper analysis and characterization of AA from ECG recordings requires, as a first step, the cancellation of ventricular activity (VA). The present contribution demonstrates the appropriateness of ICA to solve this problem based on three considerations: firstly AA and VA are generated by independent bioelectric sources, secondly AA and VA are subgaussian and supergaussian activities, respectively, and finally the surface ECG can be regarded as an instantaneous linear mixing process. After ICA algorithm application to recordings from 7 patients in AF, we prove that the AA source can be identified using a kurtosis-based reordering of the separated sources and a ulterior spectral analysis for those sources with subgaussian kurtosis. 1.