<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/5009" mdate="2010-01-23 00:00:00"> <author>Moustafa A. Bani-Hasan and Yasser M. Kadah and Fatma M. El-Hefnawi</author> <title>Identification of Cardiac Arrhythmias using Natural Resonance Complex Frequencies</title> <pages>19 - 25</pages> <year>2010</year> <volume>4</volume> <number>1</number> <journal>International Journal of Biomedical and Biological Engineering</journal> <ee>https://publications.waset.org/pdf/5009</ee> <url>https://publications.waset.org/vol/37</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>An electrocardiogram (ECG) feature extraction system based on the calculation of the complex resonance frequency employing Pronys method is developed. Pronys method is applied on five different classes of ECG signals arrhythmia as a finite sum of exponentials depending on the signals poles and the resonant complex frequencies. Those poles and resonance frequencies of the ECG signals arrhythmia are evaluated for a large number of each arrhythmia. The ECG signals of lead II (ML II) were taken from MITBIH database for five different types. These are the ventricular couplet (VC), ventricular tachycardia (VT), ventricular bigeminy (VB), and ventricular fibrillation (VF) and the normal (NR). This novel method can be extended to any number of arrhythmias. Different classification techniques were tried using neural networks (NN), K nearest neighbor (KNN), linear discriminant analysis (LDA) and multiclass support vector machine (MCSVM).</abstract> <index>Open Science Index 37, 2010</index> </article>