Abstract
The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents inter- and intra-observer variability as well as uncertainty in the classification of unreassuring or risky FHR recordings. Given the clinical relevance of the interpretation of FHR traces as well as the role of FHR as a marker of fetal wellbeing autonomous nervous system development, many different approaches for computerized processing and analysis of FHR patterns have been proposed in the literature. The objective of this review is to describe the techniques, methodologies, and algorithms proposed in this field so far, reporting their main achievements and discussing the value they brought to the scientific and clinical community. The review explores the following two main approaches to the processing and analysis of FHR signals: traditional (or linear) methodologies, namely, time and frequency domain analysis, and less conventional (or nonlinear) techniques. In this scenario, the emerging role and the opportunities offered by Artificial Intelligence tools, representing the future direction of EFM, are also discussed with a specific focus on the use of Artificial Neural Networks, whose application to the analysis of accelerations in FHR signals is also examined in a case study conducted by the authors.
Highlights
A review of linear and nonlinear methods for the analysis of FHRV has been carried out, providing an overview of the basic principles, the main pros and cons, and some of the relevant results achieved in the literature
The results of the examined studies revealed that none of the techniques available were demonstrated to be absolutely better than the others
The application of different indices can bring more information, enhancing and improving the understanding of the complex dynamics involved in the control of the fetal heart rhythm; on the other hand, the proposed combined approaches lack integration and standardization
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Electronic fetal monitoring (EFM), commonly known as cardiotocography (CTG), was developed in the 1960s with the aim of assessing a fetus’s health before and/or during labor. The fetal status is assessed through the monitoring of fetal heart rate (FHR) and uterine contractions simultaneously. Many research works can be found around this issue; this topic is still important and interesting since biomedical research aims to continuously improve diagnostic techniques. Despite its widespread use, there is not yet a final shared consensus about neither the best recording procedure (even if photoplethysmography seems to be very promising) [1] nor the best signal processing technique [2]
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