• DocumentCode
    527681
  • Title

    Hybrid hidden Markov models for ECG segmentation

  • Author

    Shi, Wu ; Kheidorov, Igor

  • Author_Institution
    Coll. of Mech. & Power Eng., Harbin Univ. of Sci. & Technol., Harbin, China
  • Volume
    6
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    3323
  • Lastpage
    3328
  • Abstract
    The new and reliable method of electrocardiogram segmentation was developed. This method has an important application to diagnostics of critical heart diseases and investigation of new drugs effect on heart. It uses powerful mathematical techniques including wavelet transforms, neural networks and hidden Markov models. The method was tested on signals from freely available QT database and showed the results, which are very close to electrocardiogram segmentation performed by heart specialists.
  • Keywords
    electrocardiography; hidden Markov models; medical signal processing; neural nets; wavelet transforms; ECG segmentation; critical heart diseases; electrocardiogram segmentation; hybrid hidden Markov models; neural networks; wavelet transforms; Databases; Electrocardiography; Heart; Hidden Markov models; Training; Wavelet transforms; Electrocardiogram; hidden Markov models; neural networks; segmentation; wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583618
  • Filename
    5583618
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=527681