Utilizing wavelet transform and support vector machine for detection of the paradoxical splitting in the second heart sound

被引:0
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作者
Bassam Al-Naami
Jamal Al-Nabulsi
Hani Amasha
John Torry
机构
[1] Hashemite University,Department of Biomedical Engineering
[2] University of Sussex,Department of Engineering and Design, School of Science and Technology
关键词
Second heart sound (S2); Meyer transform; Paradoxical splitting (PS); Support vector machine (SVM); Left bundle branch block (LBBB);
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摘要
Paradoxical splitting occurs when pulmonic valve (P2) closes before the aortic valve (A2). This causes second heart sound (S2) to be a single sound during inspiration and split during exhalation. Etiology delay in aortic closure: aortic stenosis, volume overload of left ventricle (LV), conduction defects in LV, and left bundle branch block (LBBB). In this article, a method was proposed in early detection of a reverse in the appearance of A2 and P2 within S2. This method is based on the time–frequency maps obtained with the continuous wavelet transform (CWT), namely, the Meyer wavelet. A number of patients with LBBB and others with fitted pacemakers were studied. The above method is combined with the support vector machine (SVM) and performance of this method is evaluated using classification accuracy (Ca), sensitivity (Se), specificity, positive, and negative predicted values. Results show that it is relatively easy to detect the reverse in A2 and P2 and the Ca and Se is 90.97 and 94.44%, respectively, for the sample of 42 patients whose data were collected from the Cardiology Department at Brighton and Sussex University Hospital in England.
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页码:177 / 184
页数:7
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