Screening system for heart valve disease

The first method applied by physician and cardiologists to detect heart disease is heart sound auscultation. However the skill of auscultation takes many years to acquire. Acknowledging the importance of heart sound auscultation, this research is conducted to develop a screening system that can cl...

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Main Author:	Mohd Zubir, Suboh
Format:	Thesis
Language:	English
Subjects:	Screening system Heart disease Heart screening system Heart > Diseases Heart sound auscultation
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31262/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31262/2/Full%20text.pdf
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spelling	my-unimap-312622014-01-16T13:40:15Z Screening system for heart valve disease Mohd Zubir, Suboh The first method applied by physician and cardiologists to detect heart disease is heart sound auscultation. However the skill of auscultation takes many years to acquire. Acknowledging the importance of heart sound auscultation, this research is conducted to develop a screening system that can classify normal and abnormal heart sound as well as categorizing the abnormal heart sound signal into four common categories of heart valve disease. The diseases are Aortic Regurgitation (AR), Aortic Stenosis (AS), Mitral Regurgitation (MR) and Mitral Stenosis (MS). The screening system is able to perform automated process of segmentation, feature extraction and classification of the heart sound signals. The segmentation process that is based on the time properties of the heart sound is introduced in this study to produce samples for feature extraction. The sample is converted to frequency domain and power spectrum of the signal is calculated. Power spectrum of the signal is used to get the heart sound features using cross-correlation method. The proposed method is a robust method where samples duration, cycle sequence and amplitude of the heart sound and murmur are not significantly affecting the power spectrum itself. The extracted frequency features are classified using standard Multi-Layer Perceptron (MLP) network and hierarchical Multi-Layer Perceptron network. Classification accuracy obtained from hierarchical MLP network is 100%, better than standard MLP network with accuracy of 85.71%. This is due to the complexity in classification of 5 types of heart sound signals has been reduced to two parts by using Hierarchical MLP network. A complete system that includes the process of segmentation, feature extraction and segmentation of the heart sound signal is developed in PC based platform and implemented in an embedded system. The embedded system is consists of electronic stethoscope, multimedia board (VC21PC1) and a single board computer (VCMX212) as the core. Efficiency of both PC based and embedded system is investigated in this study. A total of 646 samples from 39 subjects have been used in this study. The results show that both PC based and embedded system has produced 96.3%, 92.59% and 94.44% of screening specificity, sensitivity and accuracy for normal and abnormal classification, respectively. This showed that the proposed method is good and reliable. However, for specific classification on the other 4 type of abnormal heart sound signal, the PC based system has produced 94.44% accuracy while the embedded system only produced 87.04% accuracy. The reason is that a few approximations were applied in calculating the features and output of the MLP network. Comparison is also made with other existing systems and it is found that the proposed system has produced a comparable screening accuracy (94.44%) for normal and abnormal classification and generally better accuracy for heart valve diseases classification (87.04%). Direct comparison cannot be made because the data and method used by the other researchers are totally different. Universiti Malaysia Perlis (UniMAP) 2011 Thesis en http://dspace.unimap.edu.my:80/dspace/handle/123456789/31262 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31262/1/Page%201-24.pdf 6fb6de5ce76cab6fdc71937b6d991926 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31262/2/Full%20text.pdf dcfa3167ff536b4252e57a2f88a16933 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31262/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 Screening system Heart disease Heart screening system Heart --Diseases Heart sound auscultation School of Mechatronic Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
topic	Screening system Heart disease Heart screening system Heart --Diseases Heart sound auscultation
spellingShingle	Screening system Heart disease Heart screening system Heart --Diseases Heart sound auscultation Mohd Zubir, Suboh Screening system for heart valve disease
description	The first method applied by physician and cardiologists to detect heart disease is heart sound auscultation. However the skill of auscultation takes many years to acquire. Acknowledging the importance of heart sound auscultation, this research is conducted to develop a screening system that can classify normal and abnormal heart sound as well as categorizing the abnormal heart sound signal into four common categories of heart valve disease. The diseases are Aortic Regurgitation (AR), Aortic Stenosis (AS), Mitral Regurgitation (MR) and Mitral Stenosis (MS). The screening system is able to perform automated process of segmentation, feature extraction and classification of the heart sound signals. The segmentation process that is based on the time properties of the heart sound is introduced in this study to produce samples for feature extraction. The sample is converted to frequency domain and power spectrum of the signal is calculated. Power spectrum of the signal is used to get the heart sound features using cross-correlation method. The proposed method is a robust method where samples duration, cycle sequence and amplitude of the heart sound and murmur are not significantly affecting the power spectrum itself. The extracted frequency features are classified using standard Multi-Layer Perceptron (MLP) network and hierarchical Multi-Layer Perceptron network. Classification accuracy obtained from hierarchical MLP network is 100%, better than standard MLP network with accuracy of 85.71%. This is due to the complexity in classification of 5 types of heart sound signals has been reduced to two parts by using Hierarchical MLP network. A complete system that includes the process of segmentation, feature extraction and segmentation of the heart sound signal is developed in PC based platform and implemented in an embedded system. The embedded system is consists of electronic stethoscope, multimedia board (VC21PC1) and a single board computer (VCMX212) as the core. Efficiency of both PC based and embedded system is investigated in this study. A total of 646 samples from 39 subjects have been used in this study. The results show that both PC based and embedded system has produced 96.3%, 92.59% and 94.44% of screening specificity, sensitivity and accuracy for normal and abnormal classification, respectively. This showed that the proposed method is good and reliable. However, for specific classification on the other 4 type of abnormal heart sound signal, the PC based system has produced 94.44% accuracy while the embedded system only produced 87.04% accuracy. The reason is that a few approximations were applied in calculating the features and output of the MLP network. Comparison is also made with other existing systems and it is found that the proposed system has produced a comparable screening accuracy (94.44%) for normal and abnormal classification and generally better accuracy for heart valve diseases classification (87.04%). Direct comparison cannot be made because the data and method used by the other researchers are totally different.
format	Thesis
author	Mohd Zubir, Suboh
author_facet	Mohd Zubir, Suboh
author_sort	Mohd Zubir, Suboh
title	Screening system for heart valve disease
title_short	Screening system for heart valve disease
title_full	Screening system for heart valve disease
title_fullStr	Screening system for heart valve disease
title_full_unstemmed	Screening system for heart valve disease
title_sort	screening system for heart valve disease
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Mechatronic Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31262/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/31262/2/Full%20text.pdf
_version_	1747836788713455616

Screening system for heart valve disease

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