A hybrid algorithm for heart sounds segmentation based on phonocardiogram.
For many years, heart function has been measured by the electrocardiogram (ECG) signal, while sounds produced in the heart can also contain information indicating normal or abnormal heart function. What has caused to restrict the use of the phonocardiography (PCG) signal was the lack of mastery of e...
| Publicado en: | Journal of Medical Engineering & Technology Vol. 43; no. 6; pp. 363 - 378 |
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| Autor principal: | |
| Formato: | Journal Article |
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Taylor & Francis Ltd
Aug2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139618174&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139618174 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03091902 B9Q jtl: Journal of Medical Engineering & Technology issn: 03091902 maglogo: Y pubinfo: dt: Aug2019 vid: 43 iid: 6 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 139618174 139618174 NLM31640436 10.1080/03091902.2019.1676321 NLM31640436 139618174 ppf: 363 ppct: 15 formats: tig: atl: A hybrid algorithm for heart sounds segmentation based on phonocardiogram. aug: au: Behbahani, Soroor affil: Department of Electrical Engineering, Garmsar Branch, Islamic Azad University, Garmsar, Iran sug: subj: Heart Sounds Algorithms Heart Physiology Heart Auscultation ab: For many years, heart function has been measured by the electrocardiogram (ECG) signal, while sounds produced in the heart can also contain information indicating normal or abnormal heart function. What has caused to restrict the use of the phonocardiography (PCG) signal was the lack of mastery of experts in the interpretation of these sounds, as well as its high potential for noise pollution. PCG is a non-invasive signal for monitoring physiological parameters of cardiac, which can make heart disease diagnostics more efficient. In recent years, attempts have been made to use PCG to detect heart disease independently without a need to match with the ECG. We propose a hybrid algorithm including empirical mode decomposition (EMD), Hilbert transform and Gaussian function for detecting heart sounds to distinguish first (S1) and second (S2) cardiac sounds by eliminating the effect of cardiac murmurs. In this article, 250 normal and 250 abnormal sound signals were examined. The overall positive predictivity of normal and abnormal S1 and S2 is 98.98%, 98.78, 98.78 and 98.37, respectively. Our results showed that the proposed method has a high potential for heart sounds determination, while maintains its simplicity and has a reasonable computational time. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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