title: Classification of fetal and neonatal heart rate patterns in relation to behavioural states.
abstract: For the assessment of behavioural states in the human fetus, the fetal heart rate (FHR) pattern is one of the state variables. A statistical method is described to classify FHR patterns. FHR recordings were made between 38 and 40 wk gestation. The tachogram was averaged over 3-s intervals. For FHR segments of 3 min duration the parameters of an autoregressive-moving average (ARMA) model were estimated. Simulated FHR patterns, generated by using these estimated ARMA parameters, resembled real recordings. The ARMA parameters were used as features for a retrospective classification of the FHR segments, using a linear discriminant function. The classification by the above method was compared with an independent visual classification of the FHR patterns. The computer/observer classification agreement was 85% (kappa = 0.70). These data were compared with classification results for neonatal heart rate segments. For prospective classification of FHR patterns a moving discriminant function was introduced.
mesh_terms: D001519:Behavior / Q000502:physiology*; D005260:Female; D005318:Fetal Heart / Q000502:physiology*; D005323:Fetal Monitoring; D006339:Heart Rate; D006801:Humans; D007231:Infant, Newborn; D008955:Models, Cardiovascular; D011247:Pregnancy