• DocumentCode
    674063
  • Title

    Fetal heart rate pattern in prenatal diagnosis - fetal autonomic brain age score

  • Author

    Hoyer, D. ; Schneider, Ulrich

  • Author_Institution
    Jena Univ. Hosp., Biomagn. Center, Hans Berger Clinic for Neurology, Friedrich Schiller Univ. of Jena, Jena, Germany
  • fYear
    2013
  • fDate
    22-25 Sept. 2013
  • Firstpage
    81
  • Lastpage
    84
  • Abstract
    Fetal heart rate patterns provide valuable information about normal fetal maturation. For heart rate variability (HRV) analysis to be successful in prenatal diagnosis the selection of appropriate HRV indices is required. Those indices were organized according to universal principles of developmental biology. Key characteristics of evolution and self-organization are increasing fluctuation amplitude, increasing complexity and pattern formation. Related HRV indices were used to propose a fetal autonomic brain age score (fABAS). We estimated fABAS from magnetocardiographic recordings (21.4-40.3 weeks of gestation) preclassified in quiet (n=113, 63 females) and active sleep (n=286, 145 females) by cross-validated multivariate linear regression models in a cross-sectional study. fABAS explained 66/63% (training / validation set) of the variance by age in quiet and 51/50% in active sleep. We conclude that functional autonomic brain age can be assessed based on universal developmental indices obtained from fetal heart rate patterns.
  • Keywords
    bioelectric potentials; brain; magnetocardiography; neurophysiology; regression analysis; sleep; HRV index selection; active sleep classification; cross-sectional study; cross-validated multivariate linear regression models; developmental biology; fABAS estimation; fetal autonomic brain age score; fetal heart rate pattern; fluctuation amplitude; gestation; heart rate variability analysis; magnetocardiographic recordings; normal fetal maturation; prenatal diagnosis; quiet sleep classification; self-organization; time 21.4 week to 40.3 week; Abstracts; Complexity theory; Computational modeling; Heart rate variability; Linear regression; Modulation; Standards;
  • 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
    6712416