Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks

Cardiac auscultation is widely used by physicians to evaluate cardiac functions in patients and detect the presence of abnormalities. Phonocardiogram signals (PCG) are heart signals which contain vital information about the heart and can be used effectively in diagnosing various pathological conditi...

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Main Author:	Gupta, Cota Navin.
Other Authors:	Krishnan, Shankar Muthu
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Bioengineering
Online Access:	http://hdl.handle.net/10356/5663
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Institution:	Nanyang Technological University

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record_format	dspace
spelling	sg-ntu-dr.10356-56632023-03-11T17:05:47Z Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks Gupta, Cota Navin. Krishnan, Shankar Muthu School of Mechanical and Aerospace Engineering Swaminathan, Sundaram DRNTU::Engineering::Bioengineering Cardiac auscultation is widely used by physicians to evaluate cardiac functions in patients and detect the presence of abnormalities. Phonocardiogram signals (PCG) are heart signals which contain vital information about the heart and can be used effectively in diagnosing various pathological conditions of heart valves. Computer- based analysis of heart sounds can be used for diagnostic purposes. This present study embarks on the development of an automatic diagnostic system for characterization of phonocardiogram signals which were hierarchically clustered and homomorphically segmented and classified using neural networks. There are three core parts to the system: (1) segmentation, (2) feature extraction, (3) classification. Master of Science (Biomedical Engineering) 2008-09-17T10:56:08Z 2008-09-17T10:56:08Z 2005 2005 Thesis http://hdl.handle.net/10356/5663 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Bioengineering
spellingShingle	DRNTU::Engineering::Bioengineering Gupta, Cota Navin. Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks
description	Cardiac auscultation is widely used by physicians to evaluate cardiac functions in patients and detect the presence of abnormalities. Phonocardiogram signals (PCG) are heart signals which contain vital information about the heart and can be used effectively in diagnosing various pathological conditions of heart valves. Computer- based analysis of heart sounds can be used for diagnostic purposes. This present study embarks on the development of an automatic diagnostic system for characterization of phonocardiogram signals which were hierarchically clustered and homomorphically segmented and classified using neural networks. There are three core parts to the system: (1) segmentation, (2) feature extraction, (3) classification.
author2	Krishnan, Shankar Muthu
author_facet	Krishnan, Shankar Muthu Gupta, Cota Navin.
format	Theses and Dissertations
author	Gupta, Cota Navin.
author_sort	Gupta, Cota Navin.
title	Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks
title_short	Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks
title_full	Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks
title_fullStr	Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks
title_full_unstemmed	Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks
title_sort	classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks
publishDate	2008
url	http://hdl.handle.net/10356/5663
_version_	1761781496940593152

Classification of hierarchically clustered and homomorphic segmented heart sounds using neural networks

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