Document Detail


Noninvasive acoustical detection of coronary artery disease: a comparative study of signal processing methods.
MedLine Citation:
PMID:  8262539     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Previous studies have indicated heart sounds may contain information useful in the detection of occluded coronary arteries. During diastole, coronary blood flow is maximum, and the sounds associated with turbulent blood flow through partially occluded coronary arteries should be detectable. In order to detect such sounds, recordings of diastolic heart sound segments were analyzed by using four signal processing techniques; the Fast Fourier Transform (FFT), the Autoregressive (AR), the Autoregressive Moving Average (ARMA), and the Minimum-Norm (Eigen-vector) methods. To further enhance the diastolic heart sounds and reduce background noise, an Adaptive filter was used as a preprocessor. The power ratios of the FFT method and the poles of the AR, ARMA, and Eigen-vector methods were used to diagnose patients as diseased or normal arteries using a blind protocol without prior knowledge of the actual disease states of the patients to guard against human bias. Results showed that normal and abnormal records were correctly distinguished in 56 of 80 cases using the Fast Fourier Transform (FFT), in 63 of 80 cases using the AR, in 62 of 80 cases using the ARMA method, and in 67 of 80 cases using the Eigenvector method. Among all four methods, the Eigenvector methods showed the best diagnostic performance when compared with the FFT, AR, and ARMA methods. These results confirm that high frequency acoustic energy between 300 and 800 Hz is associated with coronary stenosis.
Authors:
Y M Akay; M Akay; W Welkowitz; J L Semmlow; J B Kostis
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IEEE transactions on bio-medical engineering     Volume:  40     ISSN:  0018-9294     ISO Abbreviation:  IEEE Trans Biomed Eng     Publication Date:  1993 Jun 
Date Detail:
Created Date:  1994-01-25     Completed Date:  1994-01-25     Revised Date:  2009-11-11    
Medline Journal Info:
Nlm Unique ID:  0012737     Medline TA:  IEEE Trans Biomed Eng     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  571-8     Citation Subset:  IM    
Affiliation:
Biomedical Engineering Department, Rutgers University, Piscataway, NJ 08855.
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MeSH Terms
Descriptor/Qualifier:
Coronary Disease / diagnosis*
Fourier Analysis
Heart Auscultation / methods*
Heart Sounds / physiology
Humans
Models, Biological
Reference Values
Sensitivity and Specificity
Signal Processing, Computer-Assisted*
Transducers

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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