Tang, Q.; Chen, Z.; Ward, R.; Menon, C.; Elgendi, M.
PPG2ECGps: An End-to-End Subject-Specific Deep Neural Network Model for Electrocardiogram Reconstruction from Photoplethysmography Signals without Pulse Arrival Time Adjustments. Bioengineering 2023, 10, 630.
https://doi.org/10.3390/bioengineering10060630
AMA Style
Tang Q, Chen Z, Ward R, Menon C, Elgendi M.
PPG2ECGps: An End-to-End Subject-Specific Deep Neural Network Model for Electrocardiogram Reconstruction from Photoplethysmography Signals without Pulse Arrival Time Adjustments. Bioengineering. 2023; 10(6):630.
https://doi.org/10.3390/bioengineering10060630
Chicago/Turabian Style
Tang, Qunfeng, Zhencheng Chen, Rabab Ward, Carlo Menon, and Mohamed Elgendi.
2023. "PPG2ECGps: An End-to-End Subject-Specific Deep Neural Network Model for Electrocardiogram Reconstruction from Photoplethysmography Signals without Pulse Arrival Time Adjustments" Bioengineering 10, no. 6: 630.
https://doi.org/10.3390/bioengineering10060630
APA Style
Tang, Q., Chen, Z., Ward, R., Menon, C., & Elgendi, M.
(2023). PPG2ECGps: An End-to-End Subject-Specific Deep Neural Network Model for Electrocardiogram Reconstruction from Photoplethysmography Signals without Pulse Arrival Time Adjustments. Bioengineering, 10(6), 630.
https://doi.org/10.3390/bioengineering10060630
