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DIGITAL ANALYSIS OF CARDIAC ACOUSTIC SIGNALS IN CHILDREN

El-Segaier, Milad LU (2007) In Lund University. Faculty of Medicine. Doctoral dissertation series.
Abstract
DIGITAL ANALYSIS OF CARDIAC ACOUSTIC SIGNALS IN CHILDREN



Milad El-Segaier, MD



Division of Paediatric Cardiology, Department of Paediatrics, Lund University Hospital, Lund, Sweden



SUMMARY



Despite tremendous development in cardiac imaging, use of the stethoscope and cardiac auscultation remains the primary diagnostic tool in evaluation of cardiac pathology. With the advent of miniaturized and powerful technology for data acquisition, display and digital signal processing, the possibilities for detecting cardiac pathology by signal analysis have increased. The objective of this study was to develop a simple, cost-effective diagnostic tool for analysis of cardiac... (More)
DIGITAL ANALYSIS OF CARDIAC ACOUSTIC SIGNALS IN CHILDREN



Milad El-Segaier, MD



Division of Paediatric Cardiology, Department of Paediatrics, Lund University Hospital, Lund, Sweden



SUMMARY



Despite tremendous development in cardiac imaging, use of the stethoscope and cardiac auscultation remains the primary diagnostic tool in evaluation of cardiac pathology. With the advent of miniaturized and powerful technology for data acquisition, display and digital signal processing, the possibilities for detecting cardiac pathology by signal analysis have increased. The objective of this study was to develop a simple, cost-effective diagnostic tool for analysis of cardiac acoustic signals. Heart sounds and murmurs were recorded in 360 children with a single-channel device and in 15 children with a multiple-channel device. Time intervals between acoustic signals were measured. Short-time Fourier transform (STFT) analysis was used to present the acoustic signals to a digital algorithm for detection of heart sounds, define systole and diastole and analyse the spectrum of a cardiac murmur. A statistical model for distinguishing physiological murmurs from pathological findings was developed using logistic regression analysis. The receiver operating characteristic (ROC) curve was used to evaluate the discriminating ability of the developed model. The sensitivities and specificities of the model were calculated at different cut-off points. Signal deconvolution using blind source separation (BSS) analysis was performed for separation of signals from different sources.



The first and second heart sounds (S1 and S2) were detected with high accuracy (100% for the S1 and 97% for the S2) independently of heart rates and presence of a murmur. The systole and diastole were defined, but only systolic murmur was analysed in this work. The developed statistical model showed excellent prediction ability (area under the curve, AUC = 0.995) in distinguishing a physiological murmur from a pathological one with high sensitivity and specificity (98%). In further analyses deconvolution of the signals was successfully performed using blind separation analysis. This yielded two spatially independent sources, heart sounds (S1 and S2) in one component, and a murmur in another.



The study supports the view that a cost-effective diagnostic device would be useful in primary health care. It would diminish the need for referring children with cardiac murmur to cardiac specialists and the load on the health care system. Likewise, it would help to minimize the psychological stress experienced by the children and their parents at an early stage of the medical care. (Less)
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author
supervisor
opponent
  • docent Lundell, Bo, Astrid Lindgrens Barnsjukhus Q1:03
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Pediatri, Medicin (människa och djur), Cardiovascular system, Kardiovaskulära systemet, Pediatrics, Medicine (human and vertebrates), Heart sound detection, Logistic regression, Receiver operating characteristic curve, Signal deconvolution., Short-time Fourier transform, Cardiac acoustic signals, Time interval measurements
in
Lund University. Faculty of Medicine. Doctoral dissertation series.
pages
134 pages
publisher
Institutionen för kliniska vetenskaper, Lunds universitet
defense location
Universitetssjukhuset i Lund Föreläsningssalen, Gamla barnkliniken Barngatan 2, Lund
defense date
2007-04-20 09:00
ISSN
1652-8220
ISBN
978-91-85559-54-1
language
English
LU publication?
yes
id
b9806364-186e-4e7c-b6ef-3bf37c535767 (old id 548307)
date added to LUP
2007-09-11 13:46:59
date last changed
2016-09-19 08:44:52
@phdthesis{b9806364-186e-4e7c-b6ef-3bf37c535767,
  abstract     = {DIGITAL ANALYSIS OF CARDIAC ACOUSTIC SIGNALS IN CHILDREN<br/><br>
<br/><br>
Milad El-Segaier, MD<br/><br>
<br/><br>
Division of Paediatric Cardiology, Department of Paediatrics, Lund University Hospital, Lund, Sweden<br/><br>
<br/><br>
SUMMARY<br/><br>
<br/><br>
Despite tremendous development in cardiac imaging, use of the stethoscope and cardiac auscultation remains the primary diagnostic tool in evaluation of cardiac pathology. With the advent of miniaturized and powerful technology for data acquisition, display and digital signal processing, the possibilities for detecting cardiac pathology by signal analysis have increased. The objective of this study was to develop a simple, cost-effective diagnostic tool for analysis of cardiac acoustic signals. Heart sounds and murmurs were recorded in 360 children with a single-channel device and in 15 children with a multiple-channel device. Time intervals between acoustic signals were measured. Short-time Fourier transform (STFT) analysis was used to present the acoustic signals to a digital algorithm for detection of heart sounds, define systole and diastole and analyse the spectrum of a cardiac murmur. A statistical model for distinguishing physiological murmurs from pathological findings was developed using logistic regression analysis. The receiver operating characteristic (ROC) curve was used to evaluate the discriminating ability of the developed model. The sensitivities and specificities of the model were calculated at different cut-off points. Signal deconvolution using blind source separation (BSS) analysis was performed for separation of signals from different sources.<br/><br>
<br/><br>
The first and second heart sounds (S1 and S2) were detected with high accuracy (100% for the S1 and 97% for the S2) independently of heart rates and presence of a murmur. The systole and diastole were defined, but only systolic murmur was analysed in this work. The developed statistical model showed excellent prediction ability (area under the curve, AUC = 0.995) in distinguishing a physiological murmur from a pathological one with high sensitivity and specificity (98%). In further analyses deconvolution of the signals was successfully performed using blind separation analysis. This yielded two spatially independent sources, heart sounds (S1 and S2) in one component, and a murmur in another.<br/><br>
<br/><br>
The study supports the view that a cost-effective diagnostic device would be useful in primary health care. It would diminish the need for referring children with cardiac murmur to cardiac specialists and the load on the health care system. Likewise, it would help to minimize the psychological stress experienced by the children and their parents at an early stage of the medical care.},
  author       = {El-Segaier, Milad},
  isbn         = {978-91-85559-54-1},
  issn         = {1652-8220},
  keyword      = {Pediatri,Medicin (människa och djur),Cardiovascular system,Kardiovaskulära systemet,Pediatrics,Medicine (human and vertebrates),Heart sound detection,Logistic regression,Receiver operating characteristic curve,Signal deconvolution.,Short-time Fourier transform,Cardiac acoustic signals,Time interval measurements},
  language     = {eng},
  pages        = {134},
  publisher    = {Institutionen för kliniska vetenskaper, Lunds universitet},
  school       = {Lund University},
  series       = {Lund University. Faculty of Medicine. Doctoral dissertation series.},
  title        = {DIGITAL ANALYSIS OF CARDIAC ACOUSTIC SIGNALS IN CHILDREN},
  year         = {2007},
}