A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals
- DOI
- 10.3390/s22030919
- Published
- 2022-01-25
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s22030919,
title = {A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals},
author = {Sakib Mahmud and Nabil Ibtehaz and Amith Khandakar and Anas M. Tahir and Tawsifur Rahman and Khandaker Reajul Islam and Md Shafayet Hossain and M. Sohel Rahman and Farayi Musharavati and Mohamed Arselene Ayari and Mohammad Tariqul Islam and Muhammad E. H. Chowdhury},
year = {2022},
journal = {Sensors},
doi = {10.3390/s22030919},
url = {https://doi.org/10.3390/s22030919}
}RIS
TY - JOUR TI - A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals AU - Sakib Mahmud AU - Nabil Ibtehaz AU - Amith Khandakar AU - Anas M. Tahir AU - Tawsifur Rahman AU - Khandaker Reajul Islam AU - Md Shafayet Hossain AU - M. Sohel Rahman AU - Farayi Musharavati AU - Mohamed Arselene Ayari AU - Mohammad Tariqul Islam AU - Muhammad E. H. Chowdhury PY - 2022 JO - Sensors DO - 10.3390/s22030919 UR - https://doi.org/10.3390/s22030919 ER -
APA
Mahmud, S., Ibtehaz, N., Khandakar, A., Tahir, A. M., Rahman, T., Islam, K. R., Hossain, M. S., Rahman, M. S., Musharavati, F., Ayari, M. A., Islam, M. T., & Chowdhury, M. E. H. (2022). A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals. Sensors. https://doi.org/10.3390/s22030919
Source records
- crossref · retrieved 2026-11-07T12:11:12.711Z