Proceedings ArticleDOI
Cardiotocograph parameter estimation using MATLAB programming
Shahad Al-Yousif,Mohd Alauddin Mohd Ali +1 more
- pp 1-3
TLDR
The determination of FHR baseline values are described which are the bases for estimating other FHR parameters and the results are compared with the estimations of two experts and a result from previous work.Abstract:
The cardiotocogram (CTG) consists of a continuous recording of fetal heart rate (FHR) and uterine contractions (UC). FHR patterns are observed manually by obstetricians during the process of cardiotocographs analyses. Changes in the FHR patterns relative to contractions provide an induction of fetal health condition. Since late 1960s CTG was introduced into clinical practice and then it has been considered as an indispensable tool for fetal monitoring. An algorithm is developed to process digital CTG using MATLAB programming to estimate FHR and to determine the parameters of the FHR pattern. This paper describes the determination of FHR baseline values which are the bases for estimating other FHR parameters. The results are compared with the estimations of two experts and a result from previous work‥read more
Citations
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Book ChapterDOI
Efficacy of Machine Learning in Predicting the Kind of Delivery by Cardiotocography
Giovanni Improta,Carlo Ricciardi,Francesco Amato,Giovanni D'Addio,Mario Cesarelli,Maria Romano +5 more
TL;DR: Preliminary results are very satisfying and encouraging; they confirm that to enrich the CTG analysis software with this methodology can help to significantly improve CTG classification.
References
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Journal ArticleDOI
Linear and nonlinear parameters for the analysisof fetal heart rate signal from cardiotocographic recordings
TL;DR: Results constitute the first step for realizing a new clinical classification system for the early diagnosis of most common fetal pathologies, based on a multiparametric FHR analysis, which includes spectral parameters from autoregressive models and nonlinear algorithms (approximate entropy).
Journal ArticleDOI
Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines
TL;DR: This research work proposes and focuses on an advanced method able to identify fetuses compromised and suspicious of developing metabolic acidosis, constituting a promising new automatic methodology for the prediction of metabolicacidosis.
Journal ArticleDOI
Computer analysis of antepartum fetal heart rate: 1. Baseline determination
TL;DR: The described procedure of baseline determination provides a solid base for automated detection of accelerations and decelerations in Fetal heart rate recordings and enables the study of the relation between the fetal heart rate pattern and fetal movements.
Proceedings ArticleDOI
Classification of cardiotocographic records by neural networks
TL;DR: Three neural classifiers are proposed to discriminate among fetal behavioral states and among normal and pathological fetal conditions, on the basis of CTG recordings, and results show very promising performance towards the prediction of fetal outcomes on the set of collected FHR signals.
Journal ArticleDOI
Computerized analysis of fetal heart rate.
TL;DR: A new computerized System (2CTG) is deveioped for the fully automated and on line analysis of F HR patterns based on a solid identification of FHR baseline and on behavioral patterns recognition.