Enhancing fetal electrocardiogram classification: A hybrid approach incorporating multimodal data fusion and advanced deep learning models
Author:
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Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17305-6.pdf
Reference63 articles.
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2. Lee S-Y, Hung Y-W, Su P-H, Lee I-P, Chen J-Y (2022) Biosignal monitoring clothing system for the acquisition of ECG and respiratory signals. IEEE Access 10:66083–66097. https://doi.org/10.1109/ACCESS.2022.3183968
3. Da Poian G, Bernardini R, Rinaldo R (2016) Separation and analysis of fetal-ECG signals from compressed sensed abdominal ECG recordings. IEEE Trans Biomed Eng 63(6):1269–1279. https://doi.org/10.1109/TBME.2015.2493726
4. Lin C, Yeh C-H, Wang C-Y et al (2019) Robust fetal heart beat detection via R-peak intervals distribution. IEEE Trans Biomed Eng 66(12):3310–3319. https://doi.org/10.1109/TBME.2019.2904014
5. Ziani S, Jbari A, Belarbi L (2017) Fetal electrocardiogram characterization by using only the continuous wavelet transform CWT. In: International conference on electrical and information technologies (ICEIT), Rabat, pp 1–6. https://doi.org/10.1109/EITech.2017.8255310
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