Discrimination of heart arrhythmias using novel features in heart rate phase space

In this paper, we try to recognize and distinguish different groups of arrhythmia using novel features which have been obtained from the heart rate's phase space in recent years. For this purpose, we used Triangular Phase Space Mapping (TPSM) and Parabolic Phase Space Mapping (PPSM). For recognition, we used three groups of 15 subjects using the Physionet database (Arrhythmia, Congestive Heart Failure (CHF), and Atrial Fibrillation (AF)) with Normal Sinus Rhythm (NSR). The obtained features discriminate arrhythmia from NSR by p<;E-5; CHF from NSR by p<;E-4; AF from NSR by p<;E-5; CHF from arrhythmia by p<;2E-2; CHF from AF by p<;6E-4; and arrhythmia from AF by p<;2E-3. The results show that PPSM is more useful in detection of cardiac arrhythmia from normal, while TPSM is more effective to recognize different arrhythmia from together.