Fetal Arrhythmia Detection based on Deep Learning using Fetal ECG Signals
Author:
Affiliation:
1. Graduate School of Science and Technology Keio University,Kanagawa,Japan,223-8522
2. Keio University,Department of Information and Computer Science,Kanagawa,Japan,223-8522
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10000063/10000593/10001697.pdf?arnumber=10001697
Reference17 articles.
1. Fetal Heart Rate Detection Using First Derivative of ECG Waveform and Multiple Weighting Functions
2. Extraction of Fetal ECG in a Non-invasive Way and Estimation of Fetal Heart Rate
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5. Non-Invasive Fetal ECG Arrhythmia Database;behar;PhysioNet,2022
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1. Hybrid deep learning methodology for fetal cardiac disease prediction;2024 10th International Conference on Communication and Signal Processing (ICCSP);2024-04-12
2. Classification of Fetal Cardiac Arrhythmia Using Heart Rate Variability and Machine Learning;2024 5th International Conference on Advancements in Computational Sciences (ICACS);2024-02-19
3. AI-Enabled Electrocardiogram Analysis for Disease Diagnosis;Applied System Innovation;2023-10-20
4. Time-scale image analysis for detection of fetal electrocardiogram;Multimedia Tools and Applications;2023-10-05
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