Classification of cardiac rhythm based on heart rate dynamics

Abstract

Cardiac rhythm classification is usually achieved using the raw electrocardiogram signal (EKG), which is not always available. By means of dynamical measures we developed a RR based classifier which is able to distinguish normal sinus rhythm (NSR), atrial fibrillation (AF) and sinus rhythm with ectopy with an accuracy of 99%, 81% and 77%, respectively, using 10-minute segments. The classifier was built on the University of Virginia (UVa) Holter database.