• DocumentCode
    1851367
  • Title

    Fetal ECG extraction from a single sensor by a non-parametric modeling

  • Author

    Niknazar, Mohammad ; Rivet, Bertrand ; Jutten, Christian

  • Author_Institution
    GIPSA-Lab., Univ. of Grenoble, St. Martin d´´Hères, France
  • fYear
    2012
  • fDate
    27-31 Aug. 2012
  • Firstpage
    949
  • Lastpage
    953
  • Abstract
    This study deals with fetal ECG and MCG extraction from a single-channel recording. A recently proposed nonparametric model to describe second-order statistical properties of ECG signal, is simplified in this paper to make it computationally faster and easier to implement. In the proposed method an ECG signal is first decomposed to sub-bands, then each sub-band is modeled separately, so less complex model is required. There is no assumption about shape of ECG signal in the model, and experimental results show its high performance on extraction of fetal cardiac signals.
  • Keywords
    electrocardiography; feature extraction; medical signal processing; nonparametric statistics; obstetrics; statistical analysis; ECG signal; MCG extraction; fetal ECG extraction; fetal cardiac signal extraction; nonparametric modeling; single channel recording; single sensor; statistical properties; Computational modeling; Correlation; Educational institutions; Electrocardiography; Kalman filters; Mathematical model; Noise; Non-parametric modeling; fetal ECG extraction; single sensor extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European
  • Conference_Location
    Bucharest
  • ISSN
    2219-5491
  • Print_ISBN
    978-1-4673-1068-0
  • Type

    conf

  • Filename
    6334034