Heart sounds clustering using a combination of temporal, spectral and geometric features

Heart murmurs are the first sign of heart valve disorders. Several studies have been conducted in recent years to automatically differentiate normal heart sounds from heart sounds with murmurs using various types of audio features. In this study, the feasibility of using a combination of temporal, s...

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Main Authors: Safara, Fatemeh, C. Doraisamy, Shyamala, Azman, Azreen, Jantan, Azrul Hazri
Format: Conference or Workshop Item
Language:English
Published: IEEE 2012
Online Access:http://psasir.upm.edu.my/id/eprint/45161/1/Heart%20sounds%20clustering%20using%20a%20combination%20of%20temporal%2C%20spectral%20and%20geometric%20features.pdf
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author Safara, Fatemeh
C. Doraisamy, Shyamala
Azman, Azreen
Jantan, Azrul Hazri
author_facet Safara, Fatemeh
C. Doraisamy, Shyamala
Azman, Azreen
Jantan, Azrul Hazri
author_sort Safara, Fatemeh
collection UPM
description Heart murmurs are the first sign of heart valve disorders. Several studies have been conducted in recent years to automatically differentiate normal heart sounds from heart sounds with murmurs using various types of audio features. In this study, the feasibility of using a combination of temporal, spectral and geometric features in clustering five types of physiological and pathological heart sounds is shown. Thirty six heart sound recordings comprising normal and abnormal heart sounds were collected from training CDs and online resources. The proposed combination of features exhibits a promising discriminatory power in phonocardiographic signals clustering.
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spelling upm.eprints-451612020-08-04T02:42:46Z http://psasir.upm.edu.my/id/eprint/45161/ Heart sounds clustering using a combination of temporal, spectral and geometric features Safara, Fatemeh C. Doraisamy, Shyamala Azman, Azreen Jantan, Azrul Hazri Heart murmurs are the first sign of heart valve disorders. Several studies have been conducted in recent years to automatically differentiate normal heart sounds from heart sounds with murmurs using various types of audio features. In this study, the feasibility of using a combination of temporal, spectral and geometric features in clustering five types of physiological and pathological heart sounds is shown. Thirty six heart sound recordings comprising normal and abnormal heart sounds were collected from training CDs and online resources. The proposed combination of features exhibits a promising discriminatory power in phonocardiographic signals clustering. IEEE 2012 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/45161/1/Heart%20sounds%20clustering%20using%20a%20combination%20of%20temporal%2C%20spectral%20and%20geometric%20features.pdf Safara, Fatemeh and C. Doraisamy, Shyamala and Azman, Azreen and Jantan, Azrul Hazri (2012) Heart sounds clustering using a combination of temporal, spectral and geometric features. In: 39th Computing in Cardiology Conference (CinC 2012), 9-12 Sept. 2012, Krakow, Poland. (pp. 217-220). https://ieeexplore.ieee.org/document/6420369/
spellingShingle Safara, Fatemeh
C. Doraisamy, Shyamala
Azman, Azreen
Jantan, Azrul Hazri
Heart sounds clustering using a combination of temporal, spectral and geometric features
title Heart sounds clustering using a combination of temporal, spectral and geometric features
title_full Heart sounds clustering using a combination of temporal, spectral and geometric features
title_fullStr Heart sounds clustering using a combination of temporal, spectral and geometric features
title_full_unstemmed Heart sounds clustering using a combination of temporal, spectral and geometric features
title_short Heart sounds clustering using a combination of temporal, spectral and geometric features
title_sort heart sounds clustering using a combination of temporal spectral and geometric features
url http://psasir.upm.edu.my/id/eprint/45161/1/Heart%20sounds%20clustering%20using%20a%20combination%20of%20temporal%2C%20spectral%20and%20geometric%20features.pdf
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