Scientific Research and Essays · 2010 · 25 citations · 7 references
MedicineMaternal HealthObstetricsBiomedical Signal ProcessingMaternal-fetal MedicineObstetric UltrasoundCardiac Signal ProcessingFetal AssessmentFetal MonitoringFetal Signal ProcessingFetal Well-being AssessmentMaternal-fetal PhysiologyBaseline Fetal Heart RateFetal CardiotocographyFetal Heart Rate Pattern InterpretationFetal Monitoring AlgorithmsFetal Physiological MonitoringHeart Rate MonitoringMonitoring Fetal Well-beingUterine Contraction Patterns
Cardiotocography (CTG) is a simultaneous recording of fetal heart rate (FHR) and uterine contractions (UC) and it is one of the most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. FHR patterns are observed manually by obstetricians during the process of CTG analyses. For the last three decades, great interest has been paid to the fetal heart rate baseline and its frequency analysis, as a base for a more objective analysis of the CTG tracings. Changes in the fetal heart rate pattern relative to contractions provide an induction of fetal condition. This paper proposed new algorithm for FHR baseline calculation. In this work, we present an algorithm for estimating baseline as one of the most important features present in the FHR signal. An algorithm based on digital CTG using Mathlab programming to estimate FHR baseline, the work in this paper rely on detection of baseline values which gives an indication of the fetal status and health condition. The results were compared with the opinion of experts (obstetricians) baseline estimation and one researcher in the same field of study. The obtained results showed slight difference with the experts opinion as a first step for further work to estimate the other parameters of the CTG. Key words: Cardiotocogram (CTG), fetal heart rate (FHR), baseline (BL), uterine contraction (UC), electronic fetal heart rate monitoring (EFM), Royal College of Obstetricians and Gynecologists (RCOG).
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George Georgoulas, Dimosthenis Stylios, Peter P. Groumpos · IEEE Transactions on Biomedical Engineering · 2006 · 144 citations
Classification of cardiotocographic records by neural networks
Giovanni Magenes, M.G. Signorini, Domenico Arduini · 2000 · 71 citations
Medicine, Cardiology, Obstetrics +15