A new approach to time dependent AR modeling of multi-frame signals and its application to diagnosis of myocardial infarction

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

Research output: Contribution to journalConference articlepeer-review

Abstract

A method for estimating spectrum transition between short-length multiframe signals in low SNR (signal-to-noise ratio) cases is presented. If the transition pattern is complex and/or there are large differences in the transition patterns among the individual sets of multiframe signals, it is difficult to estimate the transition pattern stably by the time-varying AR modeling because the results are considerably dependent on the choice of the basic functions to be used. The proposed approach uses a linear algorithm without any basic functions. Instead, the spectrum transition constraint is used, and the singular-value-decomposition-based technique is applied to obtain more accurate estimates. When this method is applied to the analysis of multiframe signals of the fourth heart sounds significant differences in the transition patterns are clearly detected in the spectra between patients with myocardial infarction and normal persons. The characteristics of these transition patterns may be applied to acoustic diagnosis of heart diseases.

Original languageEnglish
Pages (from-to)2567-2570
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
Publication statusPublished - 1990 Dec 1
Event1990 International Conference on Acoustics, Speech, and Signal Processing: Speech Processing 2, VLSI, Audio and Electroacoustics Part 2 (of 5) - Albuquerque, New Mexico, USA
Duration: 1990 Apr 31990 Apr 6

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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