Cardiotocography

Cardiotocography

Cardiotocography (CTG) is a medical test that is performed during the third trimester of pregnancy to monitor the heart rate and movements of the fetus, as well as the contractions in the uterus. This test helps to detect any signs of distress in the fetus before and during labor, and is typically done using an abdominal Doppler on the mother or a fetal scalp electrode on the baby.From: Handbook of Artificial Intelligence in Biomedical Engineering [2021], Patient Safety [2019]

Enhanced Classification Performance of Cardiotocogram Data for Fetal State Anticipation Using Evolutionary Feature Reduction Techniques

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Published in Saravanan Krishnan, Ramesh Kesavan, B. Surendiran, G. S. Mahalakshmi, Handbook of Artificial Intelligence in Biomedical Engineering, 2021

Subha Velappan, Manivanna Boopathi Arumugam, Zafer Comert

To monitor the UC and FHR and thereby the condition of the fetus such as fetal hypoxia, cardiotocography (CTG) is used (Patient.info, 2019). It is obtained from the abdomen of pregnant woman using two external probes of cardiotocograph instrument during the last trimester and also at intrapartum. Interpretation of CTG signal is done based on the parameters of the structure “DR C BRaVADO” which is listed in Table 17.1 (Geeky.medics, 2019). Figure 17.2 shows the typical CTG recorded signal containing FHR and UC (Healthnetconnections, 2019).

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Published in IETE Journal of Research, 2023

Arun Kumar, Shiban K Koul, Ranjan K Mallik

In the paper titled "Improving the Performance of Classifiers by Ensemble Techniques for the Premature Detection of Unusual Birth Outcomes from Cardiotocography," the authors propose techniques to reduce the infant mortality rate during the early stages of pregnancy. The fetal heart rates from subjects were compiled into datasets. The authors used the datasets, and classifiers such as K-nearest neighbour, Decision tree, Naive Bayes, and Random forest machine to classify normal, suspect, and pathologic cases. Inferences are drawn from the study regarding the efficacy of classification.

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Enhanced Classification Performance of Cardiotocogram Data for Fetal State Anticipation Using Evolutionary Feature Reduction Techniques

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