• DocumentCode
    744086
  • Title

    Method of fetal electrocardiogram extraction based on ν-support vector regression

  • Author

    Liang Han ; Xiu-juan Pu ; Xiao-jun Chen

  • Author_Institution
    Coll. of Commun. Eng., Chongqing Univ., Chongqing, China
  • Volume
    9
  • Issue
    5
  • fYear
    2015
  • Firstpage
    430
  • Lastpage
    439
  • Abstract
    A new method based on v-support vector regression (v-SVR) is proposed to extract the fetal electrocardiogram (FECG) from the abdominal signal recorded at the abdominal areas of the pregnant woman. The maternal electrocardiogram (MECG) component in the abdominal signal is a non-linearly transformed version of the MECG and the non-linear transform is estimated by v-SVR. The optimal estimation of the MECG component is obtained by the MECG undergoing the estimated non-linear transform. Then the FECG is extracted by subtracting the estimated MECG component from the abdominal signal. The method is validated by the experiments on both synthetic and real electrocardiogram (ECG) signals. The visual results and signal-to-noise ratio (SNR) are used to evaluate the performance of the FECG extraction methods. The experimental results indicated that the proposed method can be used for extracting the FECG from the abdominal signal.
  • Keywords
    electrocardiography; feature extraction; medical signal processing; nonlinear estimation; obstetrics; regression analysis; support vector machines; FECG extraction method; SNR; abdominal area; abdominal signal recording; fetal electrocardiogram extraction method; maternal electrocardiogram; nonlinear transform estimation; optimal MECG component estimation; pregnancy; signal-to-noise ratio; v-SVR; v-support vector regression;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IET
  • Publisher
    iet
  • ISSN
    1751-9675
  • Type

    jour

  • DOI
    10.1049/iet-spr.2013.0201
  • Filename
    7127126