• DocumentCode
    3273991
  • Title

    HHT based lung sound crackle detection and classification

  • Author

    Li, Zhenzhen ; Du, Minghui

  • Author_Institution
    Coll. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
  • fYear
    2005
  • fDate
    13-16 Dec. 2005
  • Firstpage
    385
  • Lastpage
    388
  • Abstract
    Crackles are discontinuous adventitious lung sounds, characterized by waveforms with a rapid onset and short duration. Traditional approaches to detect and classify crackles are mainly from the morphological aspect, however, the sharp patterns of crackles in frequency domain were overlooked. In this paper we employ the innovative HHT method to detect and classify crackles. By detecting peaks in time-frequency distribution derived from HHT, segments are extracted, then, crackles can be identified and classified efficiently. Relevant theories, methods and experimental results are given in detail.
  • Keywords
    Hilbert transforms; acoustic signal detection; acoustic signal processing; bioacoustics; lung; medical signal detection; medical signal processing; time-frequency analysis; Hilbert Huang transform; lung sound crackle detection; sound classification; time-frequency distribution; Acoustical engineering; Diseases; Educational institutions; Explosives; Frequency domain analysis; Lungs; Signal analysis; Spectral analysis; Time frequency analysis; Wavelet analysis; Detection and classification; Hilbert Huang Transform; Lung sound Crackles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Signal Processing and Communication Systems, 2005. ISPACS 2005. Proceedings of 2005 International Symposium on
  • Print_ISBN
    0-7803-9266-3
  • Type

    conf

  • DOI
    10.1109/ISPACS.2005.1595427
  • Filename
    1595427