ECG classification with modification of higher-order hjorth descriptors

Conference proceedings article

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Publication Details

Author list: Wannawijit I., Kaiwansil S., Ruthaisujaritkul S., Yingthawornsuk T.

Publisher: Hindawi

Publication year: 2019

Start page: 564

End page: 571

Number of pages: 8

ISBN: 9781728156866

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084840921&doi=10.1109%2fSITIS.2019.00095&partnerID=40&md5=e49b7f8c1dff7abf389733dda6ef7abf

Languages: English-Great Britain (EN-GB)

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Abstract

According to ECG signal that refers to a recording of the electrical changes that accompany each cardiac cycle so it can be used to detect and classify heart diseases. In this research, Hjorth Descriptors, which consists of 5 parameters: Activity, Mobility, Complexity, Chaos and Hazard, is used as the estimators for feature extraction. To show the comparative classifications, the Least-Squares (LS), Maximum-Likelihood (ML), Radial Basis Function Network (RBF) and Support Vector Machine (SVM) classifiers were evaluated for their performance in classification. There were three specific types of ECG signal samples, which are Normal Sinus Rhythm (NSR), Atrial Fibrillation (AF) and Congestive Heart Failure (CHF), analyzed and classified. Experiment results show that the alternative Hjorth descriptor could gain more insight of different significance among various types of ECG waveforms representing the heart function in affective condition. ฉ 2019 IEEE.

Keywords

Ecg signal, Hjorth hazard descriptor