Improving the performance of continuous non-invasive estimation of blood pressure using ECG and PPG

Blood pressure (BP) is one of the vital signs for assessing the cardiovascular health condition of a person. In recent years, the continuous non-invasive monitoring of BP is of great interest in routine and critical bedside monitoring. Previous studies have shown that pulse transit time (PTT), time taken by the pressure wave to travel between two arterial locations can be a potential indicator of the BP changes. However, hemodynamic factors (HDF) and regulatory factors (RF) influence the changes in BP. In this paper, we propose a model considering the PTT, hemodynamic and regulatory factors derived from Photoplethysmogram (PPG) and Electrocardiogram (ECG) for the better estimation of BP compared to the baseline model using PTT alone. All experiments in this work were performed using ECG, PPG, Arterial Blood Pressure waveforms from Multi-parameter Intelligent Monitoring in Intensive Care (MIMIC) II database. BP was estimated using linear regression and its coefficients were calculated for each subject. In comparison to the baseline system using PTT alone, the system using PTT, HDF and RF as the input parameters achieves a reduction in the mean absolute error (MAE) and the root mean square error (RMSE) by 6.36% and 4.98% absolute for systolic BP and 12.28% and 28.23% absolute respectively for diastolic BP. The results suggest that the quality of BP estimation using PTT, HDF and RF is improved compared to the baseline system using PTT alone.