Literature DB >> 8484565

Noninvasive characterization of the sound pattern caused by coronary artery stenosis using FTF/FAEST zero tracking filters: normal/abnormal study.

M Akay1, Y M Akay, W Welkowitz, J L Semmlow, J Kostis.   

Abstract

In this article, a new approach has been proposed to investigate the extraction of useful information from diastolic heart sounds caused by partially occluded coronary arteries. This method, which estimates and tracks the zeros (poles) of the diastolic heart sounds directly, takes advantage of the FTF/FAEST (Fast Transversal Filters/Fast a Posteriori Error Sequential) technique which possesses the fast convergence property of the Recursive Least Square (RLS) method and the computational simplicity of the Least Mean Square (LMS) method. In previous studies, the main assumption was that the diastolic heart sounds were a stationary process. Since the production of the heart sounds were a stationary process. Since the production of the heart sounds is not a stationary process, a new approach that performs well not only for stationary but also for nonstationary processes can be required. This requirement can be satisfied by the adaptive FTF/FAEST zero tracking method which provides fast and stable convergence as well as computational efficiency since the adaptive FTF/FAEST zero tracking method is based on the exact minimization of least squares criteria and the filter weights of this method are optimal at each time instant. The zero trajectories of the diastolic heart sounds were used to diagnose patients as diseased or normal. Results showed that the normal and abnormal records were incorrectly distinguished in only 6 of 35 cases using a blind protocol where analysis was done without knowledge of the actual disease states of the patients. The most discriminant time region of the zero trajectories of the diastolic heart sounds associated with coronary artery disease was between 200 and 300 msec after the second heart sound during the diastolic period.

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Year:  1993        PMID: 8484565     DOI: 10.1007/bf02367612

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  21 in total

1.  Noninvasive detection of coronary stenoses before and after angioplasty using eigenvector methods.

Authors:  M Akay; J L Semmlow; W Welkowitz; M D Bauer; J B Kostis
Journal:  IEEE Trans Biomed Eng       Date:  1990-11       Impact factor: 4.538

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Authors:  D P Giddens; R F Mabon; R A Cassanova
Journal:  Circ Res       Date:  1976-07       Impact factor: 17.367

3.  Detection of coronary occlusions using autoregressive modeling of diastolic heart sounds.

Authors:  M Akay; J L Semmlow; W Welkowitz; M D Bauer; J B Kostis
Journal:  IEEE Trans Biomed Eng       Date:  1990-04       Impact factor: 4.538

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Authors:  J F Sangster; C M Oakley
Journal:  Br Heart J       Date:  1973-08

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Authors:  M M Kartchner; L P McRae; F D Morrison
Journal:  Arch Surg       Date:  1973-04

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Authors:  T O Cheng
Journal:  Ann Intern Med       Date:  1970-04       Impact factor: 25.391

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Authors:  R S Lees; G S Myers
Journal:  Adv Intern Med       Date:  1982

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Authors:  A M Khalifa; D P Giddens
Journal:  J Biomech       Date:  1981       Impact factor: 2.712

9.  Noninvasive detection of coronary artery disease using parametric spectral analysis methods.

Authors:  J L Semmlow; M Akay; W Welkowitz
Journal:  IEEE Eng Med Biol Mag       Date:  1990

10.  On the prediction of epileptic seizures.

Authors:  Z Rogowski; I Gath; E Bental
Journal:  Biol Cybern       Date:  1981       Impact factor: 2.086

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  1 in total

1.  The clinical evaluation of the CADence device in the acoustic detection of coronary artery disease.

Authors:  Joseph L Thomas; Michael Ridner; Jason H Cole; Jeffrey W Chambers; Sabahat Bokhari; Demetris Yannopoulos; Morton Kern; Robert F Wilson; Matthew J Budoff
Journal:  Int J Cardiovasc Imaging       Date:  2018-06-23       Impact factor: 2.357

  1 in total

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