Abstract
To further explore the application of advanced signal processing techniques to the noninvasive detection of coronary artery disease, 30 patients (10 angioplasty and 20 normal or abnormal) were tested using autoregressive moving average (ARMA) modelling of the disastolic heart sound data. It is during diastole that coronary blood flow is maximum and sounds associated with turbulent blood flow through partially occluded coronary arteries would be loudest. Model parameters (the power spectral density (PSD) functions and the poles of the ARMA method) were used to separate the normal patients from the abnormal patients in the normal/ abnormal study, or to decide whether the recordings were made before or after angioplasty in the angioplasty study. The decisions were made ‘blind’, without knowledge of the actual disease states of the patients for the normal/abnormal study and without prior knowledge of whether a given recording was made before or after angioplasty for the angioplasty study. Results from the angioplasty and the normal/abnormal studies showed that pre- and post-angioplasty records were correctly distinguished in 8 out of 10 cases, and normal and abnormal records were correctly distinguished in 17 of 20 cases. These results also confirmed that high frequency energy above 400 Hz is probably associated with coronary stenosis.
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Akay, M., Bauer, M., Semmlow, J. L., Welkowitz, W. andKostis, J. (1988a) AR modeling of diastolic heart sound.Proc. IEEE Frontiers in Medicine, New Orleans, 72–175.
Akay, M., Bauer, M., Semmlow, J. L., Welkowitz, W. andKostis, J. (1988b) Analysis of diastolic heart sounds before and after angioplasty.Proc. IEEE Frontiers in Medicine, New Orleans, 257–260.
Akay, M., Semmlow, J. L., Welkowitz, W. andKostis, J. (1989) Parametric analysis of diastolic heart sounds before and after angioplasty.Proc. IEEE Frontiers in Medicine, Seattle, 51–53.
Akay, M., Semmlow, J. L., Welkowitz, W., Bauer, M. andKostis, J. (1990a) Detection of coronary occlusions using AR modelling of diastolic heart sounds.IEEE Trans. Biomed. Eng.,BME-37, 366–373.
Akay, M., Semmlow, J. L., Welkowitz, W., Bauer, M. andKostis, J. (1990b) Noninvasive detection of coronary occlusions using eigenvector methods before and after angioplasty.IEEE Trans. on Biomed. Eng.,BME-37, 1095–1104.
Akay, M. (1990) Noninvasive detection of coronary artery disease using advanced signal processing methods. Ph.D. Dissertation, Rutgers University, Piscataway, New Jersey.
Box G. andPierce, D. (1970) Distribution of residual autocorrelations in autoregressive-integrated moving average time series models.J. Am. Statist. Assoc.,64, 122–145.
Bruzzone, S. P. andKaveh, M. (1984) Information tradeoffs in using the sample autocorrelation function in ARMA parameter estimation.IEEE Trans. Acoustics, Speech, Signal Processing,ASSP-32, 701–715.
Cheng, T. O. (1970) Diagnostic murmur caused by coronary artery stenosis.Ann. Intern. Med.,72, 543–546.
Dock, W. andZoneraich, S. (1967) A diastolic murmur arising in a stenosed coronary artery.Am. J. of Med.,42, 617.
Duncan, G. W., Gruber, T. O., Dewey, C. F., Myers, G. S. andLees, R. S. (1975) Evaluation of cartoid stenosis by phonoangiography.New England J. of Med.,27, 1124–1128.
Friedlander, B. andPorat, (1984) Modifield Yule-Walker of ARMA spectral estimator.IEEE Trans. Aerospace, Electron, Syst.,AES-20, 158–172.
Giddens, D. P., Mabon, R. F. andCassanova, R. A. (1976) Measurements of disordered flows distal to subtotal vascular stenoses in the thoracic aortas of dogs.Circulation Research,39(1), 112–119.
Izraelevitz, D. andLim J. S. (1983) Spectral characteristics of the overdetermined normal equation method for spectral estimation. Proc. 2nd ASSP Spectral Estimator Workshop, 49–54.
Kartchner, M. M., McRae, L. P., Morrison, F. D. (1973) Noninvasive detection and evaluation of carotid occlusive disease.Arch. Surg.,106, 528–535.
Kaveh, M. (1979) High resolution estimator for noisy signals.IEEE Trans. Acoustic, Speech, Signal Processing,ASSP-27, 286–297.
Kaveh, M. andBruzzone, S. P. (1981) A comparative overview of ARMA spectral estimators. Proc. 1st ASSP Spectral Estimation Workshop, 2.4.1–2.4.8.
Kay, S. M. andMarple, S. L. (1981) Spectral analysis: a modern perspective.Proc. IEEE,69, 1380–1419.
Kendall, M. andStuart, A. (1977)The advanced theory of statistics. 4th edition, Griffin and Co., London.
Khalifa, A. M. A. andGiddens, D. P. (1981) Characterization of poststenotic flow disturbances.J. Biomechanics,14, 275–296.
Kurtz, K. J. (1984) Dynamic vascular auscultation.Am. J. Med.,76, 1066–1074.
Lees, R. S. andDewey, Jr.C. F. (1970) Phonoangiography: A new noninvasive diagnostic method for studying arterial disease.Proc. Natl. Acad. Sci.,67, 935–942.
Lees, R. S. andMyers, G. S. (1982) Noninvasive diagnosis of arterial disease.Adv. Intern.,23, 475–509.
Padmanabhan, V., Fisher, R., Semmlow, J. L., Welkowitz, W. andKostis, J. (1989) High sensitivity PCG transducer for extended frequency applications.Proc. IEEE Frontiers in Medicine, Seattle, 57–59.
Sangster, J. F. andOakley, C. M. (1973) Diastolic murmur of coronary artery stenosis.Br. Heart J.,35, 840–844.
Semmlow, J. L., Welkowitz, W., Kostis, J., Mackenzie, J. W. (1983) Coronary artery disease-correlates between diastolic auditory characteristic and coronary artery stenoses.IEEE Trans. Biomed. Eng.,BME-30, 136–139.
Semmlow, J. L., Akay, M. andWelkowitz, W. (1990) Noninvasive detection of CAD using parametric analysis methods.IEEE, EMBS Magazine,9, 33–37.
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Akay, M., Welkowitz, W., Semmlow, J.L. et al. Application of the ARMA method to acoustic detection of coronary artery disease. Med. Biol. Eng. Comput. 29, 365–372 (1991). https://doi.org/10.1007/BF02441656
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DOI: https://doi.org/10.1007/BF02441656