Literature DB >> 8836480

Developments in CTG analysis.

H P Van Geijn1.   

Abstract

FHR monitoring has been the subject of many debates. The technique, in itself, can be considered to be accurate and reliable both in the antenatal period, when using the Doppler signal in combination with autocorrelation techniques, and during the intrapartum period, in particular when the FHR signal can be obtained from a fetal ECG electrode placed on the presenting part. The major problems with FHR monitoring relate to the reading and interpretation of the CTG tracings. Since the FHR pattern is primarily an expression of the activity of the control by the central and peripheral nervous system over cardiovascular haemodynamics, it is possibly too indirect a signal. In other specialities such as neonatology, anaesthesiology and cardiology, monitoring and graphic display of heart rate patterns have not gained wide acceptance among clinicians. Digitized archiving, numerical analysis and even more advanced techniques, as described in this chapter, have primarily found a place in obstetrics. This can be easily explained, since the obstetrician is fully dependent on indirectly collected information regarding the fetal condition, such as (a) movements experienced by the mother, observed with ultrasound or recorded with kinetocardiotocography (Schmidt, 1994), (b) perfusion of various vessels, as assessed by Doppler velocimetry, (c) the amount of amniotic fluid or (d) changes reflected in the condition of the mother, such as the development of gestation-induced hypertension and (e) the easily, continuously obtainable FHR signal. It is of particular comfort to the obstetrician that a normal FHR tracing reliably predicts the birth of the infant in a good condition, which makes cardiotocography so attractive for widespread application. However, in the intrapartum period, many traces cannot fulfil the criteria of normality, especially in the second stage. In this respect, cardiotocography remains primarily a screening and not so much a diagnostic method. As long as continuous monitoring of fetal acid-base balance has not been extensively tested in clinical practice, microblood sampling of the fetal presenting part (Saling, 1994) is a useful adjunct. The problem with non-normal tracings is that their significance is very often unclear. They may indicate serious fetal distress, finally resulting in preventable destruction of critical areas in the fetal brain and damage to various organs; or, on the contrary, they may indicate temporary changes in cardiovascular control as a reaction to the intermittent effects on fetal haemodynamics of, for example, uterine contractions, whether or not in combination with partial or complete compression of umbilical cord vessels or the vessels on the chorionic plate (van Geijn, 1994). Many factors influence the FHR and its variability, which further complicates the interpretation of FHR patterns; some have been discussed here in some detail. Undoubtedly, there is a need for quantitative and objective FHR analysis, as long as it does not lead to erroneous results. Close collaboration between engineers and clinicians is a prerequisite for further advances in this field. Decision support systems certainly have a future but only if they are able to take into account a large set of clinical data and can combine it with data obtained from FHR signals and other parameters referring to the fetal condition, such as fetal growth, Doppler velocimetry, amniotic fluid volume and biochemical and biophysical data obtained from the mother. Basic technical concepts inherent in computerized CTG analysis, such as sampling rate (Chang et al, 1995), signal loss, artefact detection (van Geijn et al, 1980), further processing of intervals, archiving in digitized format and monitor display, should receive considerable attention. There is still a long way to go until decision support systems find their way into obstetric practice. Further developments can only be achieved thanks to efforts of many basic and clinical researchers, wo

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Year:  1996        PMID: 8836480     DOI: 10.1016/s0950-3552(96)80033-2

Source DB:  PubMed          Journal:  Baillieres Clin Obstet Gynaecol        ISSN: 0950-3552


  7 in total

1.  Foetal heart rate power spectrum response to uterine contraction.

Authors:  M Romano; P Bifulco; M Cesarelli; M Sansone; M Bracale
Journal:  Med Biol Eng Comput       Date:  2006-02-21       Impact factor: 2.602

Review 2.  Monitoring fetal maturation-objectives, techniques and indices of autonomic function.

Authors:  Dirk Hoyer; Jan Żebrowski; Dirk Cysarz; Hernâni Gonçalves; Adelina Pytlik; Célia Amorim-Costa; João Bernardes; Diogo Ayres-de-Campos; Otto W Witte; Ekkehard Schleußner; Lisa Stroux; Christopher Redman; Antoniya Georgieva; Stephen Payne; Gari Clifford; Maria G Signorini; Giovanni Magenes; Fernando Andreotti; Hagen Malberg; Sebastian Zaunseder; Igor Lakhno; Uwe Schneider
Journal:  Physiol Meas       Date:  2017-02-10       Impact factor: 2.833

3.  A Review of Fetal ECG Signal Processing; Issues and Promising Directions.

Authors:  Reza Sameni; Gari D Clifford
Journal:  Open Pacing Electrophysiol Ther J       Date:  2010-01-01

4.  Fetal vibroacoustic stimulation in computerized cardiotocographic analysis: the role of short-term variability and approximate entropy.

Authors:  Maria Laura Annunziata; Mariamaddalena Scala; Natascia Giuliano; Salvatore Tagliaferri; Olga Carmela Maria Imperato; Francesca Giovanna Esposito; Marta Campanile; Andrea Di Lieto
Journal:  J Pregnancy       Date:  2012-01-16

5.  An integrated approach based on advanced CTG parameters and Doppler measurements for late growth restriction management.

Authors:  Giovanni Magenes; Giuseppe Maria Maruotti; Maria Gabriella Signorini; Giuseppina Esposito; Nicolò Pini; Salvatore Tagliaferri; Marta Campanile; Fulvio Zullo
Journal:  BMC Pregnancy Childbirth       Date:  2021-11-16       Impact factor: 3.007

6.  A deep learning mixed-data type approach for the classification of FHR signals.

Authors:  Edoardo Spairani; Beniamino Daniele; Maria Gabriella Signorini; Giovanni Magenes
Journal:  Front Bioeng Biotechnol       Date:  2022-08-08

Review 7.  DeepFHR: intelligent prediction of fetal Acidemia using fetal heart rate signals based on convolutional neural network.

Authors:  Zhidong Zhao; Yanjun Deng; Yang Zhang; Yefei Zhang; Xiaohong Zhang; Lihuan Shao
Journal:  BMC Med Inform Decis Mak       Date:  2019-12-30       Impact factor: 2.796

  7 in total

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