Classification of Atrio-Ventricular Reentrant Tachycardia using intracardiac signals

Electrophysiology study (EPS) has been serving as a diagnostic and curative tool for rhythm-related cardiac diseases for more than few decades now. Clinical EPS requires intense knowledge of numerous protocols and run-time analysis of various parameters in order to find the root-cause of the problem. The Intracardiac Electrograms available during EPS are investigated for abnormal activations. A particular sequence of the abnormal activations hints to a specific disease. This crucial diagnosis requires a high level of expertise. In this paper, an automated algorithm to detect Atrio-Ventricular Reentrant Tachycardia (AVRT), a type of Supraventricular Tachycardia (SVT), has been proposed to assist the beginners and support the decisions of the experts of EPS. After studying the underlying medical mechanisms, exploring the electrograms formed by reentrant circuit and analyzing temporal progressions of cardiac activations of AVRT, a novel algorithm exploiting the above relationships is presented. The algorithm detects AVRT with 87.06% sensitivity.