The temporal characteristics of the acoustic signal created by turbulent blood flow in occluded coronary arteries

A. M. Smith, J. L. Semmlow, W. Welkowitz, J. B. Kostis, V. Padmanabhan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

An acoustic method to noninvasively diagnose coronary artery disease was used to differentiate between pre- and postangioplasty patients. Signal processing included the use of an analysis window which isolated segments of diastole when sounds associated with coronary occlusions are maximal, and a power spectral density function estimated by autoregressive modeling. Using a seven-weight model and a resonant accelerometer microphone, diagnostic information was provided by the spectral energy contained in a high-frequency (400-800 Hz) spectral peak (P2). Analysis windows were shifted over a range of diastolic segments to determine the relationship between P2 magnitude and window position (time). It was determined that P2 variation within a patient gives rise to a temporal relationship similar to that of the left coronary artery blood flow profile.

Original languageEnglish (US)
Title of host publicationBiomedical Engineering Perspectives
Subtitle of host publicationHealth Care Technologies for the 1990's and Beyond
PublisherPubl by IEEE
Pages571-572
Number of pages2
Editionpt 2
ISBN (Print)0879425598
StatePublished - 1990
EventProceedings of the 12th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Philadelphia, PA, USA
Duration: Nov 1 1990Nov 4 1990

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 2
ISSN (Print)0589-1019

Other

OtherProceedings of the 12th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CityPhiladelphia, PA, USA
Period11/1/9011/4/90

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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