Name
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. |
Year | Venue | Keywords |
|---|---|---|
2013 | 2013 COMPUTING IN CARDIOLOGY CONFERENCE (CINC) | sleep,neurophysiology,regression analysis |
Field | DocType | Volume |
Prenatal diagnosis,Magnetocardiography,Fetus,Internal medicine,Heart rate variability,Cardiology,Bayesian multivariate linear regression,Gestation,Fetal Heart Rate Pattern,Heart rate,Medicine,Endocrinology | Conference | 40 |
ISSN | Citations | PageRank |
2325-8861 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dirk Hoyer | 1 | 39 | 12.37 |
| Uwe Schneider | 2 | 3 | 1.44 |