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Mahmud S, Ibtehaz N, Khandakar A, Tahir AM, Rahman T, Islam KR, Hossain MS, Rahman MS, Musharavati F, Ayari MA, et al. A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals. Sensors. 2022; 22(3):919. https://doi.org/10.3390/s22030919

Mahmud, Sakib, Nabil Ibtehaz, Amith Khandakar, Anas M. Tahir, Tawsifur Rahman, Khandaker Reajul Islam, Md Shafayet Hossain, M. Sohel Rahman, Farayi Musharavati, Mohamed Arselene Ayari, and et al. 2022. "A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals" Sensors 22, no. 3: 919. https://doi.org/10.3390/s22030919

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, 22(3), 919. https://doi.org/10.3390/s22030919