• DocumentCode
    3321757
  • Title

    Cycle Identification and Artifact Detection in Tidal Breathing Signals

  • Author

    Wang, Zuojun ; Ding, Yanwu ; Parham, Douglas F. ; Lee, Kanghee

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Wichita State Univ., Wichita, KS, USA
  • fYear
    2011
  • fDate
    10-12 May 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, we introduce a novel cycle identification algorithm based on the Matlab programming to automatically identify cycles in tidal breathing signals. The algorithm is designed in three steps using filtering, derivatives, and other signal processing techniques. To verify the effectiveness of the proposed algorithm, its result are compared with those of cycles identified manually by an expert human coder. Simulations results have shown that, despite the complexity in the respiratory signals, the proposed algorithm can identify cycles correctly and efficiently.
  • Keywords
    filtering theory; mathematics computing; signal processing; Matlab programming; artifact detection; cycle identification; cycle identification algorithm; derivatives; expert human coder; filtering; respiratory signals; signal processing techniques; tidal breathing signals; Algorithm design and analysis; Biomedical engineering; Encoding; Humans; Programming; Signal processing; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2151-7614
  • Print_ISBN
    978-1-4244-5088-6
  • Type

    conf

  • DOI
    10.1109/icbbe.2011.5780258
  • Filename
    5780258