Pulse Transit Time detected from the first derivative of PPG predicted SBP and DBP with mean errors of ±3.96 mmHg and ±6.88 mmHg, respectively.
Effect estimate: R-squared 0.593 for SBP and 0.416 for DBP
Overnight continuous blood pressure measurement provides simultaneous monitoring of blood pressure and sleep architecture. By this means, we are able to investigate whether different sleep events are associated to blood pressure fluctuations. In this paper, we used the Pulse Transit Time (PTT) to develop and evaluate functions for measurement of blood pressure. We focused on the first and second derivatives of fingertip Photoplethysmography (PPG) recordings to detect PPG critical points. By applying R wave of ECG and PPG critical points, we created two PTT-based models for estimation of systolic and diastolic blood pressure (SBP and DBP). Seven subjects polysomnography datasets that contained PPG, ECG and blood pressure recordings were utilised to validate and compare developed PTT-BP functions. Results found that if the peak of the first derivative of PPG (VPG) was considered as the pulse pressure arrival point, the resulted PTT (PTTV) would more accurately predict both SBP and DBP. The average R-squared coefficient for SBP and DBP were correspondingly 0.593 and 0.416. The obtained mean error for PTTV based functions in SBP was ±3.96 mmHg with standard deviation of 1.41 mmHg and in DBP was ±6.88 mmHg with standard deviation of 3.03 mmHg. We concluded PTT detected from VPG is a reliable and suitable maker for overnight continuous blood pressure monitoring.
Shahrbabaki et al. (Mon,) reported a other. Pulse Transit Time (PTT) based models using first derivative of PPG (VPG) was evaluated on Estimation of systolic and diastolic blood pressure (SBP and DBP) (R-squared 0.593 for SBP and 0.416 for DBP). Pulse Transit Time detected from the first derivative of PPG predicted SBP and DBP with mean errors of ±3.96 mmHg and ±6.88 mmHg, respectively.