Noninvasive acoustical detection of coronary artery disease: a comparative study of signal processing methods

@article{Akay1993NoninvasiveAD,
  title={Noninvasive acoustical detection of coronary artery disease: a comparative study of signal processing methods},
  author={Y. M. Akay and Metin Akay and Walter Welkowitz and J L Semmlow and J. Kostis},
  journal={IEEE Transactions on Biomedical Engineering},
  year={1993},
  volume={40},
  pages={571-578}
}
Previous studies have indicated that, during diastole, the sounds associated with turbulent blood flow through partially occluded coronary arteries should be detectable. To detect such sounds, recordings of diastolic heart sound segments were analyzed using four signal processing techniques: the fast Fourier transform (FFT) autoregressive (AR), autoregressive moving-average (ARMA), and minimum-norm (eigenvector) methods. To further enhance the diastolic heart sounds and reduce background noise… CONTINUE READING
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