Fetal QRS Complexes Detection Using Deep Learning Technique
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42835-023-01682-x.pdf
Reference25 articles.
1. Wang S, Zhang S, Li Z, Huang L, Wei Z (2020) Automatic digital ECG signal extraction and normal QRS recognition from real scene ECG images. Comput Methods Progr Biomed 187:1–32
2. Brablik J, Kahankova R, Martinek R (2019) Influence of system configuration on the quality of non-invasive fetal electrocardiography measurement. IFAC-PapersOnLine 52(27):421–426
3. do Vale Madeiro JP, Marques JAL, Han T, Pedrosa RC (2020) Evaluation of mathematical models for QRS feature extraction and QRS morphology classification in ECG signals. Measurement 156:1–29
4. Huque ASA, Ahmed KI, Mukit MA, Mostafa R (2019) HMM-based supervised machine learning framework for the detection of fECG R-R peak locations. IRBM 40(3):157–166
5. Alshebly YS, Nafea M (2020) Isolation of fetal ECG signals from abdominal ECG using wavelet analysis. IRBM 41(5):252–260
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