Application of adaptive FTF/FAEST zero tracking filters to noninvasive characterization of the sound pattern caused by coronary artery stenosis before and after angioplasty

This article presents a new signal processing application that can be used for acoustical detection of coronary artery disease before and after angioplasty. The adaptive Autoregressive (AR) method based on the FTF/FAEST (Fast transversal filters/Fasta posteriori error sequential techniques) is used to track acoustical behavior associated with coronary occlusions. Using the amplitude trajectory of the second pole pair of this method, 9 out of 10 angioplasty patients were correctly identified using a blind protocol without prior knowledge of whether a given recording was made before and after angioplasty. These results were obtained from signals located between 200 and 300 msec after the end of the second heart sound during the diastolic period.

[1]  R. V. Mises,et al.  Mathematical Theory of Probability and Statistics , 1966 .

[2]  W. Siegenthaler,et al.  Nonoperative dilatation of coronary-artery stenosis: percutaneous transluminal coronary angioplasty. , 1979, The New England journal of medicine.

[3]  S. W. Kelly,et al.  Beat-to-beat detection of His-Purkinje system signals using adaptive filters , 2006, Medical and Biological Engineering and Computing.

[4]  William Francis Ganong,et al.  Review of Medical Physiology , 1969 .

[5]  K. J. Kurtz Dynamic vascular auscultation. , 1984, The American journal of medicine.

[6]  Lees Rs,et al.  Noninvasive diagnosis of arterial disease. , 1982 .

[7]  D. Giddens,et al.  Characterization and evolution poststenotic flow disturbances. , 1981, Journal of biomechanics.

[8]  J. Kostis,et al.  Application of the ARMA method to acoustic detection of coronary artery disease , 1991, Medical and Biological Engineering and Computing.

[9]  John L. Semmlow,et al.  High sensitivity PCG transducer for extended frequency applications , 1989, Images of the Twenty-First Century. Proceedings of the Annual International Engineering in Medicine and Biology Society,.

[10]  J. Semmlow,et al.  Noninvasive detection of coronary stenoses before and after angioplasty using eigenvector methods , 1990, IEEE Transactions on Biomedical Engineering.

[11]  Sophocles J. Orfanidis,et al.  Optimum Signal Processing: An Introduction , 1988 .

[12]  Arye Nehorai,et al.  Adaptive pole estimation , 1990, IEEE Trans. Acoust. Speech Signal Process..

[13]  S. Bruzzone,et al.  Information tradeoffs in using the sample autocorrelation function in ARMA parameter estimation , 1984 .

[14]  J. Kostis,et al.  Coronary Artery Disease - Correlates Between Diastolic Auditory Characteristics and Coronary Artery Stenoses , 1983, IEEE Transactions on Biomedical Engineering.

[15]  M M Kartchner,et al.  Noninvasive detection and evaluation of carotid occlusive disease. , 1973, Archives of surgery.

[16]  George Carayannis,et al.  A fast sequential algorithm for least-squares filtering and prediction , 1983 .

[17]  Chi Chung Ko,et al.  A simple fast adaptive zero tracking algorithm , 1990 .

[18]  I. Good,et al.  Mathematical Theory of Probability and Statistics , 1966 .

[19]  M. P. Judkins,et al.  Transluminal Treatment of Arteriosclerotic Obstruction: Description of a New Technic and a Preliminary Report of Its Application , 1964, Circulation.

[20]  I. Gath,et al.  On the prediction of epileptic seizures , 1981, Biological Cybernetics.

[21]  T O Cheng,et al.  Diastolic murmur caused by coronary artery stenosis. , 1970, Annals of internal medicine.

[22]  M. P. Judkins,et al.  Transluminal Treatment of Arteriosclerotic Obstruction , 1989 .

[23]  T. Kailath,et al.  Fast, recursive-least-squares transversal filters for adaptive filtering , 1984 .

[24]  M. Akay,et al.  Noninvasive detection of coronary artery disease using advanced signal processing techniques , 1991, Annals of Biomedical Engineering.

[25]  R. Lees,et al.  Phonoangiography: a new noninvasive diagnostic method for studying arterial disease. , 1970, Proceedings of the National Academy of Sciences of the United States of America.

[26]  W. Welkowitz,et al.  Detection of coronary occlusions using autoregressive modeling of diastolic heart sounds , 1990, IEEE Transactions on Biomedical Engineering.

[27]  Sophocles J. Orfanidis,et al.  Zero-tracking adaptive filters , 1986, IEEE Trans. Acoust. Speech Signal Process..

[28]  R. Lees,et al.  Noninvasive diagnosis of arterial disease. , 1982, Advances in internal medicine.

[29]  B. Widrow,et al.  Multichannel adaptive filtering for signal enhancement , 1981 .

[30]  B. Friedlander,et al.  The Modified Yule-Walker Method of ARMA Spectral Estimation , 1984, IEEE Transactions on Aerospace and Electronic Systems.

[31]  C. Oakley,et al.  Diastolic murmur of coronary artery stenosis. , 1973, British heart journal.

[32]  W Dock,et al.  A diastolic murmur arising in a stenosed coronary artery. , 1967, The American journal of medicine.

[33]  John E. Markel,et al.  Linear Prediction of Speech , 1976, Communication and Cybernetics.

[34]  W. Welkowitz,et al.  Noninvasive detection of coronary artery disease using parametric spectral analysis methods , 1990, IEEE Engineering in Medicine and Biology Magazine.

[35]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .