Database of A-EGM signals for manual and automated complexity evaluation of complex fractionated atrial electrograms

Abstract

Radiofrequency ablation (RFA) has become a more-less standardized surgery routine, which is used by cardiologists and electrophysiologists (EPs) to treat atrial fibrillation (AF) disease. EPs can also evaluate a complexity of an atrial electrogram (A-EGM) signal to find places that trigger or sustain AF in left atria of the heart, this is usually done in real time during RAF of AF. This is a complexity evaluation of A-EGM, which is done by EPs based on an observation of time series of amplitudes of measured bipolar A-EGM. Such investigation of A-EGMs plays more and more important role in clinical practice to successfully treat AF. For a proper treatment of AF it is crucial to understand more the propagation of waves in left atria during AF and to study how we can get this information from the observation of A-EGM signal, either manually by EPs or automatically by a programmed algorithm. To study these phenomenons the database of A-EGM signals for its complexity evaluation is substantial. Such data- base should handle thousands of A-EGMs that are correctly described by experts. This will enable to study and develop new strategies for AF treatment as well as it can help during learning process of students of EP that will be performing the RAF of AF in the future during their regular work. We started to develop such kind of A-EGM signals database and in this paper we describe its basics and architecture. The database is at current time the only of its kind around globe and is fully applicable for described tasks and even more. In the future, when it is filled by real and well described A-EGM signals it could help to reduce time of RAF of AF and reduce costs of the treatment and a suffering of patients. © 2013 Springer-Verlag.