• DocumentCode
    674086
  • Title

    Fetal ECG extraction from abdominal recordings using array signal processing

  • Author

    Haghpanahi, Masoumeh ; Borkholder, David A.

  • Author_Institution
    Rochester Inst. of Technol., Rochester, NY, USA
  • fYear
    2013
  • fDate
    22-25 Sept. 2013
  • Firstpage
    173
  • Lastpage
    176
  • Abstract
    An algorithm to automatically locate QRS complexes in noninvasive fetal ECG signals is described and was entered in the PhysioNet/CinC 2013 “Noninvasive Fetal ECG” challenge. The algorithm is based on an iterative subspace decomposition and filtering of the maternal ECG components from the recordings of a set of electrodes placed on the mother´s abdomen. Once the maternal components are removed, a novel merging technique is applied to merge the recordings and generate a signal with a higher SNR to perform fetal peak detection. The algorithm produces an annotation file for each data set containing the location of the fetal QRS complexes in that set. The final results indicate that the algorithm is able to detect fetal peaks under different scenarios and for variety of devices and signals encountered in clinical practice.
  • Keywords
    array signal processing; biomedical electrodes; electrocardiography; feature extraction; filtering theory; iterative methods; medical signal detection; obstetrics; Noninvasive Fetal ECG challenge; PhysioNet/CinC 2013; SNR; abdominal recording; annotation file; array signal processing; clinical practice; electrode recordings; fetal ECG extraction; fetal QRS complexes; fetal peak detection; iterative subspace decomposition; maternal ECG component filtering; maternal component removal; merging technique; mother abdomen; noninvasive fetal ECG signals; Electrocardiography; Indexes; Kalman filters; Merging; Noise; Signal processing algorithms; Time-frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing in Cardiology Conference (CinC), 2013
  • Conference_Location
    Zaragoza
  • ISSN
    2325-8861
  • Print_ISBN
    978-1-4799-0884-4
  • Type

    conf

  • Filename
    6712439