• DocumentCode
    1141054
  • Title

    A new approach to time dependent AR modeling of signals and its application to analysis of the fourth heart sound

  • Author

    Kanai, Hiroshi ; Chubachi, Noriyoshi ; Kido, Ken´iti ; Koiwa, Yoshiro ; Takagi, Takehiko ; Kikuchi, Junichi ; Takishima, Tamotsu

  • Author_Institution
    Dept. of Electr. Eng., Tohoku Univ., Sendai, Japan
  • Volume
    40
  • Issue
    5
  • fYear
    1992
  • fDate
    5/1/1992 12:00:00 AM
  • Firstpage
    1198
  • Lastpage
    1205
  • Abstract
    The authors present a method for estimating spectrum transition between short-length signals of succeeding frames in low-SNR cases when the transition pattern is complex and/or there are large differences in the transition patterns among the individual sets of multiframe signals. The present approach uses a linear algorithm without any basic functions. Instead, the authors use the spectrum transition constraint, and the singular value decomposition. (SVD)-based technique is applied to obtain more accurate estimates. For the analysis of multiframe signals of the fourth heart sounds obtained during a stress test, significant differences in the transition patterns are clearly detected in the spectra between patients with myocardial infarction and normal persons The significant characteristics of these transition patterns may be applied to acoustic diagnosis of heart disease
  • Keywords
    acoustic signal processing; bioacoustics; cardiology; physiological models; spectral analysis; SNR; SVD; acoustic diagnosis; fourth heart sound; heart disease; linear algorithm; multiframe signals; myocardial infarction; short-length signals; singular value decomposition; spectrum transition constraint; spectrum transition estimation; stress test; time dependent AR modeling; transition pattern; Acoustic signal detection; Acoustic testing; Cardiac disease; Heart; Medical diagnostic imaging; Myocardium; Pattern analysis; Signal analysis; Signal to noise ratio; Stress;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.134481
  • Filename
    134481