Article

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

2022-07-22

Abstract excerpt

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 analysis or as a clinical alert system to assist the practitioner. Three models were developed and used to detect (i) FSs on the MHR channel (the FSMHR model), (ii) the MHR...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e03e3b5a-cc71-5bda-ad46-a5eb69f751b8
DOI: 10.20944/preprints202207.0131.v2

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Use of Deep Learning to Detect the Maternal Heart Rate and False Signals on Fetal Heart Rate RecordingsDOI 10.20944/preprints202207.0131.v2Read

Monitoring Fetal Heart Rate based on Fine-tuned Transfer Learning and Hybrid ModelsSemantic proximity Read

Deep Learning-Based Inference of Uterine Contractions from Maternal ECGSemantic proximity Read

Deep Learning Based Fetal Distress Detection from Time Frequency Representation of Cardiotocogram Signal Using Morse WaveletSemantic proximity Read

Preterm Birth Risk Stratification through Longitudinal Heart Rate and HRV Monitoring in Daily LifeSemantic proximity Read

Rapid detection of fetal compromise using input length invariant deep learning on fetal heart rate signalsSemantic proximity Read

Unveiling the unborn: Advancing fetal health classification through machine learningSemantic proximity Read

Extraction of fetal heart beat sounds in abdominal phonocardiograms using deep attention transformer networkSemantic proximity Read

Deep learning model for prenatal congenital heart disease (CHD) screening generalizes to the community setting and outperforms clinical detectionSemantic proximity Read

Can machine learning or deep learning discover novel signatures of illness in continuous cardiorespiratory monitoring data?Semantic proximity Read

An efficient monitoring of HELLP syndrome pre-eclampsia in wireless sensors networksSemantic proximity Read

Non-Invasive Arterial Blood Pressure Waveform Generation in Critically Ill Patients: A Sensor-Based Deep Learning ApproachSemantic proximity Read

Deep learning for detecting congenital heart disease in the fetusSemantic proximity Read