Heart murmur detection and analysis using multipoint auscultation system

The study of phonocardiogram (PCG) in diagnosing valvular heart disease has gathered increasing attention over the past few years. Heart sound auscultation is performed at the primary care center by physician and the results are subjected to the skills and hearing ability. This has caused unnecessar...

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Main Author: Ismail, Kamarulafizam
Format: Thesis
Language:English
Published: 2015
Subjects:
Online Access:http://eprints.utm.my/id/eprint/54702/1/KamarulafizamIsmailPFBME2015.pdf
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spelling my-utm-ep.547022020-11-03T08:47:38Z Heart murmur detection and analysis using multipoint auscultation system 2015-08 Ismail, Kamarulafizam R Medicine (General) The study of phonocardiogram (PCG) in diagnosing valvular heart disease has gathered increasing attention over the past few years. Heart sound auscultation is performed at the primary care center by physician and the results are subjected to the skills and hearing ability. This has caused unnecessary referral and send home subject with potential heart disease. This issue has led to the establishment of standardized and computerized system to analyze the heart sound. This thesis investigates the optimal approach in establishing a reliable system to acquire and process heart sound to differentiate between normal and abnormal pattern. Previous studies are based on the analysis using heart sound that is recorded from single stethoscope which provides limited information regarding the heart disease. In this study, the recording based on four stethoscopes is used to record sound from four different valves with optimized analog instrumentation design. Beamforming algorithm is utilized to localize the actual source of the disease sound from all of the four recorded sound by focusing with respect to the angle of arrival of the desired disease signature. It is then followed by the implementation of Time Frequency (TF) algorithm with optimal Extended Modified B-Distribution (EMBD) kernel to suppress noises, analyze and represent the features. The experiments were conducted utilizing PCG signal that was recorded from real subject from Hospital Sultanah Aminah Johor Bahru. Each subject was screened by an echocardiogram machine. The disease was confirmed by cardiologist before the PCG recording procedure was performed. The result shows significant improvement in the quality of information that is preserved in the beamformed signal. The suggested framework is able to improve the heart murmur detection rate up to 95%. In conclusion, the localization of the exact location of the diseased sound has helped to improve the disease detection accuracy based on multi-point heart sound diagnostic system. 2015-08 Thesis http://eprints.utm.my/id/eprint/54702/ http://eprints.utm.my/id/eprint/54702/1/KamarulafizamIsmailPFBME2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:94674 phd doctoral Universiti Teknologi Malaysia, Faculty of Biosciences and Medical Engineering Faculty of Biosciences and Medical Engineering
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic R Medicine (General)
spellingShingle R Medicine (General)
Ismail, Kamarulafizam
Heart murmur detection and analysis using multipoint auscultation system
description The study of phonocardiogram (PCG) in diagnosing valvular heart disease has gathered increasing attention over the past few years. Heart sound auscultation is performed at the primary care center by physician and the results are subjected to the skills and hearing ability. This has caused unnecessary referral and send home subject with potential heart disease. This issue has led to the establishment of standardized and computerized system to analyze the heart sound. This thesis investigates the optimal approach in establishing a reliable system to acquire and process heart sound to differentiate between normal and abnormal pattern. Previous studies are based on the analysis using heart sound that is recorded from single stethoscope which provides limited information regarding the heart disease. In this study, the recording based on four stethoscopes is used to record sound from four different valves with optimized analog instrumentation design. Beamforming algorithm is utilized to localize the actual source of the disease sound from all of the four recorded sound by focusing with respect to the angle of arrival of the desired disease signature. It is then followed by the implementation of Time Frequency (TF) algorithm with optimal Extended Modified B-Distribution (EMBD) kernel to suppress noises, analyze and represent the features. The experiments were conducted utilizing PCG signal that was recorded from real subject from Hospital Sultanah Aminah Johor Bahru. Each subject was screened by an echocardiogram machine. The disease was confirmed by cardiologist before the PCG recording procedure was performed. The result shows significant improvement in the quality of information that is preserved in the beamformed signal. The suggested framework is able to improve the heart murmur detection rate up to 95%. In conclusion, the localization of the exact location of the diseased sound has helped to improve the disease detection accuracy based on multi-point heart sound diagnostic system.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Ismail, Kamarulafizam
author_facet Ismail, Kamarulafizam
author_sort Ismail, Kamarulafizam
title Heart murmur detection and analysis using multipoint auscultation system
title_short Heart murmur detection and analysis using multipoint auscultation system
title_full Heart murmur detection and analysis using multipoint auscultation system
title_fullStr Heart murmur detection and analysis using multipoint auscultation system
title_full_unstemmed Heart murmur detection and analysis using multipoint auscultation system
title_sort heart murmur detection and analysis using multipoint auscultation system
granting_institution Universiti Teknologi Malaysia, Faculty of Biosciences and Medical Engineering
granting_department Faculty of Biosciences and Medical Engineering
publishDate 2015
url http://eprints.utm.my/id/eprint/54702/1/KamarulafizamIsmailPFBME2015.pdf
_version_ 1747817706556489728