• DocumentCode
    2628005
  • Title

    QRS Wave Recognition Based on United Algorithm of Mathematical Morphology and Wavelet

  • Author

    Xiaoxia, Hao ; Runjing, Zhou

  • Author_Institution
    Dept. of Autom., Inner Mongolia Univ., Hohhot, China
  • Volume
    6
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    218
  • Lastpage
    222
  • Abstract
    QRS wave recognition is very important in ECG signal analysis. The united algorithm of mathematical morphology and wavelet is brought in this paper to solve the low recognition rate problems of the abnormal QRS waves, such as high T waves, various R waves and the waves including myoelectric noise. Firstly, the ECG signal is processed by mathematical morphology algorithm so that the R wave will be more obvious, and other waves that change smoothly will be mapped in horizontal axis. Then, the wavelet analysis algorithm is used to locate the QRS wave in both time domain and frequency domain. This algorithm doesn´t only remain excellent resolution in frequency, but also avoid interference of pseudo difference signal for test results of wavelet transformation. The ECG signals of different cases in the database are experimented with the united Algorithms and other two commonly used algorithms at the end of this paper, and the results show that the united algorithms can increase the recognition rate.
  • Keywords
    electrocardiography; mathematical morphology; medical signal processing; wavelet transforms; ECG signal analysis; QRS wave recognition; mathematical morphology; united algorithm; wavelet; Algorithm design and analysis; Electrocardiography; Frequency domain analysis; Morphology; Signal analysis; Signal processing; Signal resolution; Time domain analysis; Wavelet analysis; Wavelet domain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.732
  • Filename
    5170693