Adaptive blood pressure estimation from wearable PPG sensors using peripheral artery pulse wave velocity measurements and multi-channel blind identification of local arterial dynamics

Abstract

A method for estimating pulse wave velocity (PWV) using circulatory waveform signals derived from multiple photoplethysmograph (PPG) sensors is described. The method employs two wearable in-line PPG sensors placed at a known distance from one another at the ulnar and digital artery. A technique for calibrating the measured pulse wave velocity to arterial blood pressure using hydrostatic pressure variation is presented. Additionally, a framework is described for estimating local arterial dynamics using PPG waveforms and multi-channel blind system ID. Initial results implementing the method on data derived from a human subject at different arterial pressures is presented. Results show that the method is capable of measuring the changes in arterial PWV that result from fluctuations in mean arterial pressure.

Advanced Bio-Inspired System for Noninvasive Cuff-Less Blood Pressure Estimation from Physiological Signal Analysis

“…It is well known that blood pressure can be estimated by the analysis of the waves produced at the heart propagated over the arteries. The Moens-Korteweg equation gives the pulse-wave velocity [1] as a function of vessel and fluid characteristics [2], as well as the arterial wall elasticity from which a measure of the average pressure may be obtained [3]. However, this approach (and similar ones based on analytic models) is inapplicable, as it requires the precise knowledge of some vessel physical parameters for each patient.…”

“…Experiments showed that RAS is a promising calibration parameter to provide more accurate PTT-SBP estimation. An interesting method was proposed in [7], in which an approach for BP monitoring and estimation based on the relationship between the velocity of the pulse wave [1] and the BP was described. The detection of the velocity of pulse wave was computed by the analysis of the mechanical movements of blood vessel's walls, as well as by additional information retrieved from the PPG signal.…”

“…In order to have a robust and careful analysis of that correlation, our study has been supported by physiologists and cardiologists. In the literature, it is well known that there is a correlation between the PPG signal (or other blood flow-based signals) and blood pressure, as described in some mathematical models such as the Moens-Korteweg equation previously mentioned [1]. However, by taking into account the information retrieved from physiologists and cardiologists, as well as considering preliminary results obtained by the same authors in their previous work (BI-P2RS) in [24], the authors supposed that blood pressure (both SDB and DBP) is correlated with blood flow and its velocity and acceleration in the human arteries, as both measures are related to the cardiac activity.…”

Non-Invasive Continuous Blood-Pressure Monitoring Models Based on Photoplethysmography and Electrocardiography

“…Similar to the theory of PWV, Payne et al verified that the pulse wave transit time (PWTT) was associated with blood pressure [14], and the correlation between PWTT and systolic blood pressure (SBP) was stronger than that between PWTT and diastolic blood pressure (DBP) [15,16]. McCombie presented a framework using peripheral artery PWV and blind system identification to estimate blood pressure [17]. The PWV method solved the issues of complicated device and uncomfortability; still, this model had weak generalization ability due to individual differences [18].…”

Comparative analysis of LDR and OPT 101 detectors in reflectance type PPG sensor

“…[8][9][10] There are two main PPG operational configurations namely transmission mode and a reflective mode. In transmission mode, tissue sample (fmgertip) is placed between source and detector.…”