Original title: ECG signal classification based on SVM
Authors: Smíšek, Radovan
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: Cardiovascular diseases nowadays represent the most common cause of death in Western countries. Long-term ECG recording is modern method, because it allows to detect sporadically occurring pathology. We designed an automatic classifier to detect five pathologies (AAMI standard) by SVM method. The classifier was tested on the entire MIT-BIH Arrhythmia Database with an accuracy of 99.17 %. We also compared the quality of parameters entering the classifier.
Keywords: ECG classification; MIT-BIH database; support vector machines; SVM
Host item entry: Proceedings of the 22nd Conference STUDENT EEICT 2016, ISBN 978-80-214-5350-0

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/83957

Permalink: http://www.nusl.cz/ntk/nusl-383675


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers