Dual-site Photoplethysmography Sensing for Noninvasive Continuous-time Blood Pressure Monitoring Using Artificial Neural Network

In this work, we propose dual site Photoplethysmography (PPG) sensing for blood pressure monitoring using Artificial Neural Network (ANN). The method was implemented on a microcontroller for real-time BP monitoring. The models were evaluated on 15 volunteers and the ANN model achieved a MAE±SD 0.29 ± 4.49 mmHg for SBP and 0.5±2.4 mmHg for DBP. The proposed dual PPG site ANN model exhibited superior performance and robustness in real-time tests compared to the classical ANN single-site PPG model.