MATIC - AN INTRACARDIAC TACHYCARDIA CLASSIFICATION-SYSTEM

The use of additional atrial sensing electrode together with a morphology recognition algorithm provides a significant improvement in classification performance over the current rate based algorithms used in implantable cardioverter defibrillator [ICD] devices. The classification system, called morphology and timing intracardiac classifier [MATIC], follows a classification process similar to that used by cardiologists. Timing between the atrial and ventricular channels is examined using a decision tree and forms the primary criterion for arrhythmia classification. A neural network based morphology classifier is used for cases such as ventricular tachycardia with 1:1 retrograde conduction where timing alone cannot make a reliable decision. MATIC achieves 99.6% correct classification on a database of intracardiac electrogram [ICEG] signals containing 12,483 QRS complexes recorded from 67 patients during electrophysiological studies. Arrhythmias in this database include sinus tachycardia, normal sinus rhythm, normal sinus rhythm with bundle branch block, sinus tachycardia with bundle branch block, atrial fibrillation [AF], various supraventricular tachycardias, ventricular tachycardia, ventricular tachycardia with 1:1 retrograde conduction, and ventricular fibrillation. Within these arrhythmias, there were numerous ventricular ectopic beats, fusion beats, noise, and other artifacts. MATIC addresses the classification problem from start to finish, inputs being raw intracardiac electrogram signals and the outputs being the recommended ICD therapy. Results achieved with MATIC were compared with a classifier used in the Telectronics Guardian ATP 4210, which achieved 75.9% correct classification on the same database. MATIC is simple and efficient, making it suitable for use in a low power implantable device.