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Cardiotocography

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A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals.

Sensors (Basel, Switzerland)
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 in...

Cardiotocography in Obstetrics: New Solutions for "Routine" Technology.

Sensors (Basel, Switzerland)
This work is devoted to the problems of one of the most common screening examinations used in medical practice: fetal cardiotocography (CTG). The technology of ultrasonic monitoring of fetal heart rate (HR) variations has been used for more than 70 y...

Use of Deep Learning to Detect the Maternal Heart Rate and False Signals on Fetal Heart Rate Recordings.

Biosensors
We have developed deep learning models for automatic identification of the maternal heart rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The models can be used to preprocess FHR data prior to automated analy...

A CNN-RNN unified framework for intrapartum cardiotocograph classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Prenatal fetal monitoring, which can monitor the growth and health of the fetus, is very vital for pregnant women before delivery. During pregnancy, it is crucial to judge whether the fetus is abnormal, which helps obstetric...

Artificial intelligence and machine learning in cardiotocography: A scoping review.

European journal of obstetrics, gynecology, and reproductive biology
INTRODUCTION: Artificial intelligence (AI) is gaining more interest in the field of medicine due to its capacity to learn patterns directly from data. This becomes interesting for the field of cardiotocography (CTG) interpretation, since it promises ...

Deep learning based fetal distress detection from time frequency representation of cardiotocogram signal using Morse wavelet: research study.

BMC medical informatics and decision making
BACKGROUND: Clinically cardiotocography is a technique which is used to monitor and evaluate the level of fetal distress. Even though, CTG is the most widely used device to monitor determine the fetus health, existence of high false positive result f...

OB HUB: Remote Electronic Fetal Monitoring Surveillance.

MCN. The American journal of maternal child nursing
OBJECTIVE: The purpose of this project was to implement a remote fetal surveillance unit with increased vigilance and timelier responses to electronic fetal monitor tracings to improve neonatal outcomes and increase safety.

Real-time Classification of Fetal Status Based on Deep Learning and Cardiotocography Data.

Journal of medical systems
This study uses convolutional neural networks (CNNs) and cardiotocography data for the real-time classification of fetal status in the mobile application of a pregnant woman and the computer server of a data expert at the same time (The sensor is con...

A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability.

BMC medical informatics and decision making
BACKGROUND: Intelligent cardiotocography (CTG) classification can assist obstetricians in evaluating fetal health. However, high classification performance is often achieved by complex machine learning (ML)-based models, which causes interpretability...

Intelligent classification of cardiotocography based on a support vector machine and convolutional neural network: Multiscene research.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To propose a computerized system utilizing multiscene analysis based on a support vector machine (SVM) and convolutional neural network (CNN) to assess cardiotocography (CTG) intelligently.