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Linear and nonlinear approaches to heart rate analysis near the time of birth
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Dissertation
Linear and nonlinear approaches to heart rate analysis near the time of birth
2004
Overview
Heart rate (HR) analysis has been regarded as one of the best ways to assess well-being of human beings. In this dissertation, two projects have been included. The first one is to predict fetal distress through fetal heart rate (FHR) monitoring during labor. The second one is to explore different stationarity properties of neonatal HR toward early diagnosis of neonatal sepsis. Project 1. Continuous monitoring of FHR during labor is based on the clinical experience that fetal hypoxia causes loss of FHR variation and the occurrence of decelerations late during uterine contraction. However, improved fetal outcome has not been shown for monitored fetuses and the benefit of electronic fetal monitoring (EFM) has been questioned. It was reasoned that this might be due to the qualitative nature of the current subjective interpretation of FHR records and to the large degree of intra- and inter-observer disagreement. Therefore, this project aimed to test the hypothesis that features important to clinician's interpretations might be used in a predictive diagnostic model. Project 2. The clinical diagnosis of neonatal sepsis is preceded by abnormal heart rate characteristics of transient decelerations and reduced variability, which intuitively appear to be more non-stationary than normal heart rate variability (HRV). In this context, non-stationarity was defined to be present when the observed data differed from surrogate data generated by stationarity Gaussian processes with arbitrary linear correlation. The goals were to investigate stationarity of HR, and to devise measures useful for early diagnosis of neonatal sepsis. The results of the work showed that HRV analysis was able to quantify the HR features that might be useful to predict or early diagnose fetal distress and neonatal sepsis clinically. (Abstract shortened by UMI.)
Publisher
ProQuest Dissertations & Theses
Subject
ISBN
0496087908, 9780496087907
