End-to-end trained encoder–decoder convolutional neural network for fetal electrocardiogram signal denoising
Author:
Publisher
IOP Publishing
Subject
Physiology (medical),Biomedical Engineering,Physiology,Biophysics
Link
https://iopscience.iop.org/article/10.1088/1361-6579/ab69b9/pdf
Reference50 articles.
1. Complete foetal ECG morphology recording by synchronised adaptive filtration
2. An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms
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1. Artificial Intelligence and Machine Learning in Electrophysiology—a Short Review;Current Treatment Options in Cardiovascular Medicine;2023-09-04
2. One-Dimensional W-NETR for Non-Invasive Single Channel Fetal ECG Extraction;IEEE Journal of Biomedical and Health Informatics;2023-07
3. An open-source framework for synthetic post-dive Doppler ultrasound audio generation;PLOS ONE;2023-04-27
4. Real-time amplitude spectrum area estimation during chest compression from the ECG waveform using a 1D convolutional neural network;Frontiers in Physiology;2023-04-20
5. Principles of Fetal Electrocardiography;Innovative Technologies and Signal Processing in Perinatal Medicine;2023-04-17
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