Morphologically constrained signal subspace characterization of electrograms during ventricular fibrillation

Abstract

Abstract Ventricular fibrillation (VF) is a lethal cardiac arrhythmia traditionally believed to be chaotic in nature. However, recent research studies have shown that certain events of interest during VF may exhibit local (or regional) organization. These time-varying and spatially migrating organized activities manifest themselves into different signal morphologies within electrograms acquired during VF. Performing targeted (or constrained) signal decomposition of electrograms to extract such signal morphologies associated with events of clinical interest will be of significant value. We present one such targeted adaptive signal decomposition of intra-cardiac electrograms during VF, to automatically extract morphologies previously observed in relation to the vicinity of rotor phenomenon (i.e. an event of interest during VF). Using a Gabor dictionary and Matching Pursuits (MP), the proposed method successfully performed targeted signal decomposition in highlighting signal structures that could be used to determine the ventricular electrogram's vicinity to a rotor in the epicardium. A comparative analysis using the MP with a proposed choice function ( P P