Abstract
Intrapartum fetal heart rate (FHR) monitoring constitutes a reference tool in clinical practice to assess the baby’s health status and to detect fetal acidosis. It is usually analyzed by visual inspection grounded on FIGO criteria. Characterization of intrapartum fetal heart rate temporal dynamics remains a challenging task and continuously receives academic research efforts. Complexity measures, often implemented with tools referred to as approximate entropy (ApEn) or sample entropy (SampEn), have regularly been reported as significant features for intrapartum FHR analysis. We explore how information theory, and especially auto-mutual information (AMI), is connected to ApEn and SampEn and can be used to probe FHR dynamics. Applied to a large (1404 subjects) and documented database of FHR data, collected in a French academic hospital, it is shown that (i) auto-mutual information outperforms ApEn and SampEn for acidosis detection in the first stage of labor and continues to yield the best performance in the second stage; (ii) Shannon entropy increases as labor progresses and is always much larger in the second stage; (iii) babies suffering from fetal acidosis additionally show more structured temporal dynamics than healthy ones and that this progressive structuration can be used for early acidosis detection.
Highlights
Intrapartum fetal heart rate monitoring: Because it is likely to provide obstetricians with significant information related to the health status of the fetus during delivery, intrapartum fetal heart rate (FHR) monitoring is a routine procedure in hospitals
This has triggered a large amount of research world wide aiming both to compute in a reproducible and objective way the Federation of Gynecology and Obstetrics (FIGO) criteria [2] and to devise new signal processing-inspired features to characterize FHR temporal dynamics
The second section reports the definitions of two features rooted in complexity theory: approximate entropy (ApEn) and sample entropy (SampEn), which are classically used in cardiac signal analysis
Summary
Intrapartum fetal heart rate monitoring: Because it is likely to provide obstetricians with significant information related to the health status of the fetus during delivery, intrapartum fetal heart rate (FHR) monitoring is a routine procedure in hospitals. It has been well documented that such visual inspection is prone to severe inter-individual variability and even shows a substantial intra-individual variability [4]. This reflects both that FHR temporal dynamics are complex and hard to assess and that. Difficulties in performing objective assessment of these criteria has led to a substantial number of unnecessary Caesarean sections [5] This has triggered a large amount of research world wide aiming both to compute in a reproducible and objective way the FIGO criteria [2] and to devise new signal processing-inspired features to characterize FHR temporal dynamics (cf [6,7] for reviews)
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