• DocumentCode
    591166
  • Title

    A real-time algorithm for tracking of foetal ECG sources obtained by block-on-line BSS techniques

  • Author

    Pani, Danilo ; Dessi, Alessia ; Cabras, B. ; Raffo, Luigi

  • Author_Institution
    DIEE - Dept. Electr. & Electron. Eng., Univ. of Cagliari, Cagliari, Italy
  • fYear
    2012
  • fDate
    9-12 Sept. 2012
  • Firstpage
    65
  • Lastpage
    68
  • Abstract
    The foetal ECG (FECG) can be digitally extracted in real-time from non-invasive recordings using Blind Source Separation (BSS) techniques. BSS suffers the permutation ambiguity, scrambling the estimated sources over time and then hampering the FECG visual and automated analysis. In this paper a block-on-line tracking algorithm, including an unsupervised morphological stage able of creating an average FECG beat, is presented. It allows the automatic identification of the FECG sources block-wise even in presence of permutations. The algorithm has been successfully tested on both real and synthetic signals, showing a percentage of correct foetal ECG peaks identification up to 93.44%. Its porting on the OMAP L137 embedded processor, with the OL-JADE FECG extraction algorithm, allowed the assessment of its real-time capabilities.
  • Keywords
    blind source separation; electrocardiography; medical signal processing; obstetrics; FECG automated analysis; FECG beat; FECG visual analysis; OL-JADE FECG extraction algorithm; OMAP L137 embedded processor; blind source separation technique; block-on-line BSS techniques; block-on-line tracking algorithm; foetal ECG peak identification; foetal ECG source tracking; noninvasive recordings; permutation ambiguity; real-time algorithm; synthetic signals; unsupervised morphological stage; Algorithm design and analysis; Clustering algorithms; Correlation; Electrocardiography; Noise; Real-time systems; Source separation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing in Cardiology (CinC), 2012
  • Conference_Location
    Krakow
  • ISSN
    2325-8861
  • Print_ISBN
    978-1-4673-2076-4
  • Type

    conf

  • Filename
    6420331