Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier.
Numerous studies are being conducted in recent years focusing on phonocardiographic (PCG) signals due to their capability to characterize heart sounds. These characteristics can be exploited in developing computer-aided auscultation system as a complementary tool for clinicians in diagnosis of car...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
IACSIT Press
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/30606/1/Diagnosis%20of%20heart%20valve%20disorders%20through%20trapezoidal%20features%20and%20hybrid%20classifier.pdf |
| _version_ | 1825947739902443520 |
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| author | Safara, Fatemeh C. Doraisamy, Shyamala Azman, Azreen Jantan, Azrul Hazri Sri Ranga, |
| author_facet | Safara, Fatemeh C. Doraisamy, Shyamala Azman, Azreen Jantan, Azrul Hazri Sri Ranga, |
| author_sort | Safara, Fatemeh |
| collection | UPM |
| description | Numerous studies are being conducted in recent years focusing on phonocardiographic (PCG) signals due to
their capability to characterize heart sounds. These
characteristics can be exploited in developing computer-aided auscultation system as a complementary tool for clinicians in diagnosis of cardiovascular disorders. This study proposes a new type of features to distinguish five categories of heart sounds, including normal, mitral stenosis, mitral regurgitation,aortic stenosis, and aortic regurgitation. PCG signals were collected from online resources and training CDs. Wavelet packet transform was utilized for heart sound analysis as opposed to discrete wavelet transform that has been extensively used in the previous studies. Then, trapezoidal function was calculated for deriving feature vectors. A hybrid classifier was
designed composing of three types of classifiers, multilayer
perceptron (MLP) artificial neural network, k-nearest neighbor (KNN), and support vector machine (SVM), to classify feature vectors.The promising results demonstrate the effectiveness of the proposed trapezoidal features and hybrid classifier for heart sound classification. |
| first_indexed | 2024-03-06T08:18:04Z |
| format | Article |
| id | upm.eprints-30606 |
| institution | Universiti Putra Malaysia |
| language | English English |
| last_indexed | 2024-03-06T08:18:04Z |
| publishDate | 2013 |
| publisher | IACSIT Press |
| record_format | dspace |
| spelling | upm.eprints-306062016-01-28T03:51:44Z http://psasir.upm.edu.my/id/eprint/30606/ Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier. Safara, Fatemeh C. Doraisamy, Shyamala Azman, Azreen Jantan, Azrul Hazri Sri Ranga, Numerous studies are being conducted in recent years focusing on phonocardiographic (PCG) signals due to their capability to characterize heart sounds. These characteristics can be exploited in developing computer-aided auscultation system as a complementary tool for clinicians in diagnosis of cardiovascular disorders. This study proposes a new type of features to distinguish five categories of heart sounds, including normal, mitral stenosis, mitral regurgitation,aortic stenosis, and aortic regurgitation. PCG signals were collected from online resources and training CDs. Wavelet packet transform was utilized for heart sound analysis as opposed to discrete wavelet transform that has been extensively used in the previous studies. Then, trapezoidal function was calculated for deriving feature vectors. A hybrid classifier was designed composing of three types of classifiers, multilayer perceptron (MLP) artificial neural network, k-nearest neighbor (KNN), and support vector machine (SVM), to classify feature vectors.The promising results demonstrate the effectiveness of the proposed trapezoidal features and hybrid classifier for heart sound classification. IACSIT Press 2013-11 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30606/1/Diagnosis%20of%20heart%20valve%20disorders%20through%20trapezoidal%20features%20and%20hybrid%20classifier.pdf Safara, Fatemeh and C. Doraisamy, Shyamala and Azman, Azreen and Jantan, Azrul Hazri and Sri Ranga, (2013) Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier. International Journal of Bioscience, Biochemistry and Bioinformatics, 3 (6). pp. 662-665. ISSN 2010-3638 http://www.ijbbb.org/list-42-1.html English |
| spellingShingle | Safara, Fatemeh C. Doraisamy, Shyamala Azman, Azreen Jantan, Azrul Hazri Sri Ranga, Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier. |
| title | Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier. |
| title_full | Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier. |
| title_fullStr | Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier. |
| title_full_unstemmed | Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier. |
| title_short | Diagnosis of heart valve disorders through trapezoidal features and hybrid classifier. |
| title_sort | diagnosis of heart valve disorders through trapezoidal features and hybrid classifier |
| url | http://psasir.upm.edu.my/id/eprint/30606/1/Diagnosis%20of%20heart%20valve%20disorders%20through%20trapezoidal%20features%20and%20hybrid%20classifier.pdf |
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