A PPG-Based Calibration-Free Cuffless Blood Pressure Estimation Method Using Cardiovascular Dynamics

Abstract

Traditional cuff-based sphygmomanometers for measuring blood pressure can be uncomfortable and particularly unsuitable to use during sleep. A proposed alternative method uses dynamic changes in the pulse waveform over short intervals and replaces calibration with information from photoplethysmogram (PPG) morphology to provide a calibration-free approach using a single sensor. Results from 30 patients show a high correlation of 73.64% for systolic blood pressure (SBP) and 77.72% for diastolic blood pressure (DBP) between blood pressure estimated with the PPG morphology features and the calibration method. This suggests that the PPG morphology features could replace the calibration stage for a calibration-free method with similar accuracy. Applying the proposed methodology on 200 patients and testing on 25 new patients resulted in a mean error (ME) of −0.31 mmHg, a standard deviation of error (SDE) of 4.89 mmHg, a mean absolute error (MAE) of 3.32 mmHg for DBP and an ME of −4.02 mmHg, an SDE of 10.40 mmHg, and an MAE of 7.41 mmHg for SBP. These results support the potential for using a PPG signal for calibration-free cuffless blood pressure estimation and improving accuracy by adding information from cardiovascular dynamics to different methods in the cuffless blood pressure monitoring field.

Stability of Watch-Based Blood Pressure Measurements Analyzed by Pre-Post Calibration Differences

“…n recent years, smartwatch devices equipped with photoplethysmography (PPG) technology have seen a significant rise in popularity for estimating blood pressure (BP). PPG, a non-invasive optical technique, measures blood volume changes by illuminating the skin and detecting variations in light absorption [1] [2]. Utilizing this technology, smartwatches now offer users convenient, continuous BP monitoring.…”

Non-invasive estimation of sbp pressure using a single ppg sensor and self-calibration

“…This leads to the needs for the development of noninvasive BP estimation methods and techniques using wearable PPG sensors in recent years (i.e. [2][3][4][5][6]).…”

“…In the present body of knowledge [2][3][4][5][6], a number of different features extracted from either PPG signals or its derivatives are used in the estimation model. For example, the work reported in [2] developed algorithm to estimate SBP based on ECG and PPG sensors through the extraction of many relevant features including PAT (Pulse Arrival Time), PD (Pulse Delay) as well as first and second order derivatives of PPG signals.…”

“…Blood Pressure information can be estimated using various features of PPG data noninvasively measured at the finger tips (i.e. [2][3][4][5][6]). Here, in the proposed method, two features (Systolic upstroke time -SUT, and PPG inter-beat interval -IBI as shown in Figure 1) are extracted to be used in the estimation model building of SBP which relies on the hypothesis that SBP positively correlates to Heart Rate (HR), and inversely correlates to SUT, particularly:…”

Using Data Augmentation to Improve the Accuracy of Blood Pressure Measurement Based on Photoplethysmography

“…There are mainly two kinds of data-driven BP measurement methods based on PPG: the feature-based method and the data-based method. The main idea of the featurebased method is to extract hand-crafted features, then explore the relationship between features and BP values [8][9][10]. The data-based method directly uses neural networks to fit the relationship between PPG and BP, without the need for hand-crafted feature extraction [11][12][13][14][15][16][17].…”