Ανάπτυξη συστήματος διάγνωσης εμβρυϊκής υποξίας και πρόληψης άμεσων και απώτερων σοβαρών επιπλοκών με εφαρμογή σύγχρονων τεχνικών επεξεργασίας και ανάλυσης σήματος

Abstract

In the last few years the research community has given great attention to the detection of antepartum and intrapartum fetal hypoxia, given its direct impact on both short- and long-term neonatal morbidity and mortality. The successful completion of labor depends mainly on the prompt identification of fetal hypoxia. The development of computational systems for the early diagnosis of restricted fetal oxygen supply is therefore of critical importance. This thesis involves the design and development of an innovative system for the early detection of acidosis, which was based on the fetal heart rate processing and fetal pulse oximetry analysis. The aim of the system is to comprise a computer-aided diagnostic system of fetal hypoxia and to contribute to the decision making regarding the labor completion time, in order to prevent short- and long-term neonatal complications. Specifically, the development of the system was based on the implementation of continuous wavelet transform and adaptive approximation using the matching pursuit algorithm, in order to reveal the “hidden” information conveyed in the very low frequency range of the fetal heart rate. The system involves the combination of the results of the above-mentioned processing techniques, and especially of the matching pursuit algorithm, along with the calculation of the duration of fetal arterial low oxygen saturation, applying a commonly used clustering algorithm. The proposed system is an innovative and promising approach towards the early diagnosis of fetal hypoxia, given its high specificity and positive predictive value, thus effectively addressing the major drawback of clinical cardiotocography.