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dc.contributor.author Abibullaev, Berdakh -
dc.contributor.author Kang, Won-Seok -
dc.contributor.author Lee, Seung Hyun -
dc.contributor.author An, Jinung -
dc.date.available 2017-07-11T08:20:08Z -
dc.date.created 2017-06-25 -
dc.date.issued 2010 -
dc.identifier.isbn 9788988678206 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/3967 -
dc.description.abstract In the current study we present a technique for the detection and classification of cardiac arrhythmias using biorthogonal wavelet functions and support vector machines (SVM). First, the wavelet transforms is applied to decompose the ECG signal into wavelet scales. Further, a soft thresholding technique is used to denoise and detect important cardiac events in the signal. Subsequently, we applied SVM classifier to discriminate the detected events into normal or pathological ones in the signal. Numeric computations demonstrate that the efficient wavelet pre-processing provides an accurate estimation of important physiological features of ECG and moreover it improves the SVM classification performance. -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.relation.ispartof INC2010 - The International Conference on Networked Computing, Proceeding -
dc.title Classification of cardiac arrhythmias using biorthogonal wavelet preprocessing and SVM -
dc.type Conference Paper -
dc.identifier.scopusid 2-s2.0-77954809357 -
dc.identifier.bibliographicCitation 6th International Conference on Networked Computing, INC2010, pp.332 - 336 -
dc.citation.conferenceDate 2010-05-11 -
dc.citation.conferencePlace US -
dc.citation.conferencePlace Gyeongju -
dc.citation.endPage 336 -
dc.citation.startPage 332 -
dc.citation.title 6th International Conference on Networked Computing, INC2010 -
dc.type.docType Conference Paper -

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