• DocumentCode
    2741393
  • Title

    Adaptive Modeling of Sound Transmission in the Respiratory System

  • Author

    Ciftci, K. ; Yeginer, M. ; Sen, I. ; Cini, U. ; Kahya, Y.P.

  • Author_Institution
    Institute of Biomedical Engineering, Bogazici University, Bebek, Istanbul, Turkey
  • Volume
    2
  • fYear
    2004
  • fDate
    1-5 Sept. 2004
  • Firstpage
    3824
  • Lastpage
    3827
  • Abstract
    In this study, adaptive filtering techniques have been used in an attempt to model the respiratory system. The respiratory system has been considered as a dynamic system for which input-output relationship is to be defined. Simultaneous measurement of the respiratory sounds over the trachea and posterior chest were made, with the signal from the trachea forming the input to a finite impulse response filter and the signal from the posterior chest forming the desired response of the filter. The chest cavity was stimulated with speech sounds. Least-mean square algorithm was used to update filter coefficients. The learning curves of the filter are presented in the paper. It can be concluded that adaptive filtering is a promising way to characterize transmission characteristics of the respiratory system and further improvement may be obtained if anatomical information is integrated in the modeling process.
  • Keywords
    modeling; respiration; sound transmission; Acoustical engineering; Adaptive filters; Biomedical engineering; Biomedical measurements; Finite impulse response filter; Lungs; Respiratory system; Signal generators; Speech; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
  • Print_ISBN
    0-7803-8439-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2004.1404071
  • Filename
    1404071