• DocumentCode
    3136737
  • Title

    An Automatic System for Crackles Detection and Classification

  • Author

    Lu, Xiaoguang ; Bahoura, Mohammed

  • Author_Institution
    Departement de Math-Info-Genie, Univ. du Quebec, Rimouski, Que.
  • fYear
    2006
  • fDate
    38838
  • Firstpage
    725
  • Lastpage
    729
  • Abstract
    In this paper, an automatic system for crackles detection and classification is developed. The proposed system is preceded by a stationary-nonstationary filter based on the wavelet packet transform (WPSTNST) which isolates the crackles from the vesicular sounds. The crackle analysis consists of three major steps: Firstly, a denoising filter is applied to suppress the stationary residual noise in non-stationary signal. Secondly, a new version of crackles detection based on the fractal dimension is presented. The advantage of this method is to detect crackles even they are week or overlapped. Finally, the extracted crackles are classified into fine or coarse crackles. The time-frequency analysis, the Prony model and matched wavelet analysis techniques are tested and compared in this paper
  • Keywords
    filtering theory; interference suppression; signal classification; signal denoising; signal detection; wavelet transforms; automatic system; crackle detection; denoising filter; stationary-nonstationary filter; time-frequency analysis; wavelet packet transform; Acoustic noise; Filters; Fractals; Noise reduction; Signal analysis; Testing; Time frequency analysis; Wavelet analysis; Wavelet packets; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 2006. CCECE '06. Canadian Conference on
  • Conference_Location
    Ottawa, Ont.
  • Print_ISBN
    1-4244-0038-4
  • Electronic_ISBN
    1-4244-0038-4
  • Type

    conf

  • DOI
    10.1109/CCECE.2006.277698
  • Filename
    4054681