• DocumentCode
    2132941
  • Title

    A novel method for feature extraction of crackles in lung sound

  • Author

    Li Zhenzhen ; Wu Xiaoming ; Du Minghui

  • Author_Institution
    Sch. of Biosci. & Bioeng., South China Univ. of Technol., Guangzhou, China
  • fYear
    2012
  • fDate
    16-18 Oct. 2012
  • Firstpage
    399
  • Lastpage
    402
  • Abstract
    Crackles are an important kind abnormal lung sound for detection in lung sound analysis. Focused on characteristic morphology of crackles in time-domain, a novel time-domain processing method is proposed to extract features of crackles based on the newly rising theories of Fractional Hilbert Transform. After applying the transformation of Fractional Hilbert Transform with various fractional values, exclusive timedomain features are merged and can be used as validated detection features. Experiments show great application feasibilities for such kind of wave detections. Later we use correlation functions to construct an elementary detection system, and system simulation results support the effectiveness of our work. Discussions on detection errors are followed.
  • Keywords
    Hilbert transforms; acoustic signal detection; acoustic signal processing; feature extraction; lung; medical signal detection; medical signal processing; time-domain analysis; abnormal lung sound; crackles; detection errors; elementary detection system; feature extraction; fractional Hilbert transform; lung sound analysis detection; morphology; system simulation; time-domain processing method; wave detections; Biomedical signal processing; crackle detection; lung sound analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4673-1183-0
  • Type

    conf

  • DOI
    10.1109/BMEI.2012.6512982
  • Filename
    6512982