Estimation of Pulse Transit Time as a Function of Blood Pressure Using a Nonlinear Arterial Tube-Load Model

Contactless Blood Pressure Measurement Via Remote Photoplethysmography With Synthetic Data Generation Using Generative Adversarial Networks

Remote photoplethysmography (rPPG) has been used to measure vital signs such as heart rate, heart rate variability, blood pressure (BP), and blood oxygen. Recent studies adopt features developed with photoplethysmography (PPG) to achieve contactless BP measurement via rPPG. These features can be classified into two groups: time or phase differences from multiple signals, or waveform feature analysis from a single signal. Here we devise a solution to extract the time difference information from the rPPG signal captured at 30 FPS. We also propose a deep learning model architecture to estimate BP from the extracted features. To prevent overfitting and compensate for the lack of data, we leverage a multi-model design and generate synthetic data. We also use subject information related to BP to assist in model learning. For real-world usage, the subject information is replaced with values estimated from face images, with performance that is still better than the state-of-the-art. To our best knowledge, the improvements can be achieved because of: 1) the model selection with estimated subject information, 2) replacing the estimated subject information with the real one, 3) the InfoGAN assistance training (synthetic data generation), and 4) the time difference features as model input. To evaluate the performance of the proposed method, we conduct a series of experiments, including dynamic BP measurement for many single subjects and nighttime BP measurement with infrared lighting. Our approach reduces the MAE from 15.49 to 8.78 mmHg for systolic blood pressure (SBP) and 10.56 to 6.16 mmHg for diastolic blood pressure(DBP) on a self-constructed rPPG dataset. On the Taipei Veterans General Hospital(TVGH) dataset for nighttime applications, the MAE is reduced from 21.58 to 11.12 mmHg for SBP and 9.74 to 7.59 mmHg for DBP, with improvement ratios of 48.47% and 22.07% respectively.

Development of a PPG-based hardware and software system deployable on elbow and thumb for real-time estimation of pulse transit time

Blood pressure (BP) is a vital parameter used by clinicians to diagnose issues in the human cardiovascular system. Cuff-based BP devices are currently the standard method for on-the-spot and ambulatory BP measurements. However, cuff-based devices are not comfortable and are not suitable for long-term BP monitoring. Many studies have reported a significant correlation between pulse transit time (PTT) with blood pressure. However, this relation is impacted by many internal and external factors which might lower the accuracy of the PTT method. In this paper, we present a novel hardware system consisting of two custom photoplethysmography (PPG) sensors designed particularly for the estimation of PTT. In addition, a software interface and algorithms have been implemented to perform a real-time assessment of the PTT and other features of interest from signals gathered between the brachial artery and the thumb. A preclinical study has been conducted to validate the system. Five healthy volunteer subjects were tested and the results were then compared with those gathered using a reference device. The analysis reports a mean difference among subjects equal to -3.75±7.28 ms. Moreover, the standard deviation values obtained for each individual showed comparable results with the reference device, proving to be a valuable tool to investigate the factors impacting the BP-PTT relationship.Clinical Relevance- The proposed system proved to be a feasible solution to detect blood volume changes providing good quality signals to be used in the study of BP-PTT relationship.

Personalized aortic pressure waveform estimation from brachial pressure waveform using an adaptive transfer function

BACKGROUND AND OBJECTIVE

The aortic pressure waveform (APW) provides reliable information for the diagnosis of cardiovascular disease. APW is often measured using a generalized transfer function (GTF) applied to the peripheral pressure waveform acquired noninvasively, to avoid the significant risks of invasive APW acquisition. However, the GTF ignores various physiological conditions, which affects the accuracy of the estimated APW. To solve this problem, this study utilized an adaptive transfer function (ATF) combined with a tube-load model to achieve personalized and accurate estimation of APW from the brachial pressure waveform (BPW).

METHODS

The proposed method was validated using APWs and BPWs from 34 patients. The ATF was defined using a tube-load model in which pulse transit time and reflection coefficients were determined from, respectively, the diastolic-exponential-pressure-decay of the APW and a piece-wise constant approximation. The root-mean-square-error of overall morphology, mean absolute errors of common hemodynamic indices (systolic blood pressure, diastolic blood pressure and pulse pressure) were used to evaluate the ATF.

RESULTS

The proposed ATF performed better in estimating diastolic blood pressure and pulse pressure (1.63 versus 1.94 mmHg, and 2.37 versus 3.10 mmHg, respectively, both P < 0.10), and produced similar errors in overall morphology and systolic blood pressure (3.91 versus 4.24 mmHg, and 2.83 versus 2.91 mmHg, respectively, both P > 0.10) compared to GTF.

CONCLUSION

Unlike the GTF which uses fixed parameters trained on existing clinical datasets, the proposed method can achieve personalized estimation of APW. Hence, it provides accurate pulsatile hemodynamic measures for the evaluation of cardiovascular function.

Validating cuffless continuous blood pressure monitoring devices

Cuff-based home blood pressure (BP) devices, which have been the standard for BP monitoring for decades, are limited by physical discomfort, convenience, and their ability to capture BP variability and patterns between intermittent readings. In recent years, cuffless BP devices, which do not require cuff inflation around a limb, have entered the market, offering the promise of continuous beat-to-beat measurement of BP. These devices take advantage of a variety of principles to determine BP, including (1) pulse arrival time, (2) pulse transit time, (3) pulse wave analysis, (4) volume clamping, and (5) applanation tonometry. Because BP is calculated indirectly, these devices require calibration with cuff-based devices at regular intervals. Unfortunately, the pace of regulation of these devices has failed to match the speed of innovation and direct availability to patient consumers. There is an urgent need to develop a consensus on standards by which cuffless BP devices can be tested for accuracy. In this narrative review, we describe the landscape of cuffless BP devices, summarize the current status of validation protocols, and provide recommendations for an ideal validation process for these devices.

Blood Pressure Measurement: From Cuff-Based to Contactless Monitoring

Blood pressure (BP) determines whether a person has hypertension and offers implications as to whether he or she could be affected by cardiovascular disease. Cuff-based sphygmomanometers have traditionally provided both accuracy and reliability, but they require bulky equipment and relevant skills to obtain precise measurements. BP measurement from photoplethysmography (PPG) signals has become a promising alternative for convenient and unobtrusive BP monitoring. Moreover, the recent developments in remote photoplethysmography (rPPG) algorithms have enabled new innovations for contactless BP measurement. This paper illustrates the evolution of BP measurement techniques from the biophysical theory, through the development of contact-based BP measurement from PPG signals, and to the modern innovations of contactless BP measurement from rPPG signals. We consolidate knowledge from a diverse background of academic research to highlight the importance of multi-feature analysis for improving measurement accuracy. We conclude with the ongoing challenges, opportunities, and possible future directions in this emerging field of research.

Cuff-less and continuous blood pressure measurement based on pulse transit time from carotid and toe photoplethysmograms

Blood pressure (BP) is a vital health parameter that varies throughout the day. As a single reading of high BP may not indicate hypertension, continuous monitoring of BP is usually recommended by medical doctors to confirm the diagnosis of hypertension. In the last few decades, researchers have investigated cuff-less and continuous BP measurements based on pulse transit time (PTT). The main purpose of this research is to develop an autoregressive (ARX) system identification (SI)-based PTT calculation model using two PPG signals acquired from carotid and toe. The signals were recorded from 65 subjects with an age range between 20 and 60 years. The results of the study have been validated in two stages. The first validation comprised the estimated BP from PTT using SI compared to the measured BP using the cuff-based method for all subjects. The results of the estimated BP using the proposed method compared to the measured BP obtained using the standard BP cuff measurement method are highly correlated to both systolic blood pressure (R² = 0.8132) and diastolic blood pressure (R² = 0.8357). The second validation consisted of comparing PTT values using system identification to the results of the PTT derived from the ECG-PPG method. The results showed that both methods are highly correlated (R² = 0.7808), and there is no significant difference between them (p < 0.05) with a slightly better PTT estimation related to DBP in the proposed method. Our results have proven that the PTT obtained from the carotid PPG and toe PPG using the system identification approach yielded SBP and DBP estimations that are consistent with the values of the conventional BP cuff method. The newly proposed method has the advantage of being cuff-less and able to provide continuous BP measurements.

Wearable Blood Pressure Sensing Based on Transmission Coefficient Scattering for Microstrip Patch Antennas

Painless, cuffless and continuous blood pressure monitoring sensors provide a more dynamic measure of blood pressure for critical diagnosis or continuous monitoring of hypertensive patients compared to current cuff-based options. To this end, a novel flexible, wearable and miniaturized microstrip patch antenna topology is proposed to measure dynamic blood pressure (BP). The methodology was implemented on a simulated five-layer human tissue arm model created and designed in High-Frequency Simulation Software “HFSS”. The electrical properties of the five-layer human tissue were set at the frequency range (2−3) GHz to comply with clinical/engineering standards. The fabricated patch incorporated on a 0.4 mm epoxy substrate achieved consistency between the simulated and measured reflection coefficient results at flat and bent conditions over the frequency range of 2.3−2.6 GHz. Simulations for a 10 g average specific absorption rate (SAR) based on IEEE-Standard for a human arm at different input powers were also carried out. The safest input power was 50 mW with an acceptable SAR value of 3.89 W/Kg < 4W/Kg. This study also explored a novel method to obtain the pulse transit time (PTT) as an option to measure BP. Pulse transmit time is based on obtaining the time difference between the transmission coefficient scattering waveforms measured between the two pairs of metallic sensors underlying the assumption that brachial arterial geometries are dynamic. Consequently, the proposed model is validated by comparing it to the standard nonlinear Moens and Korteweg model over different artery thickness-radius ratios, showing excellent correlation between 0.76 ± 0.03 and 0.81 ± 0.03 with the systolic and diastolic BP results. The absolute risk of arterial blood pressure increased with the increase in brachial artery thickness-radius ratio. The results of both methods successfully demonstrate how the radius estimates, PTT and pulse wave velocity (PWV), along with electromagnetic (EM) antenna transmission propagation characteristics, can be used to estimate continuous BP non-invasively.

Cuffless Blood Pressure Measurement

Cuffless blood pressure (BP) measurement has become a popular field due to clinical need and technological opportunity. However, no method has been broadly accepted hitherto. The objective of this review is to accelerate progress in the development and application of cuffless BP measurement methods. We begin by describing the principles of conventional BP measurement, outstanding hypertension/hypotension problems that could be addressed with cuffless methods, and recent technological advances, including smartphone proliferation and wearable sensing, that are driving the field. We then present all major cuffless methods under investigation, including their current evidence. Our presentation includes calibrated methods (i.e., pulse transit time, pulse wave analysis, and facial video processing) and uncalibrated methods (i.e., cuffless oscillometry, ultrasound, and volume control). The calibrated methods can offer convenience advantages, whereas the uncalibrated methods do not require periodic cuff device usage or demographic inputs. We conclude by summarizing the field and highlighting potentially useful future research directions. Expected final online publication date for the Annual Review of Biomedical Engineering, Volume 24 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Improving the accuracy and robustness of carotid-femoral pulse wave velocity measurement using a simplified tube-load model

Arterial stiffness, as measured by pulse wave velocity, for the early non-invasive screening of cardiovascular disease is becoming ever more widely used and is an independent prognostic indicator for a variety of pathologies including arteriosclerosis. Carotid-femoral pulse wave velocity (cfPWV) is regarded as the gold standard for aortic stiffness. Existing algorithms for cfPWV estimation have been shown to have good repeatability and accuracy, however, further assessment is needed, especially when signal quality is compromised. We propose a method for calculating cfPWV based on a simplified tube-load model, which allows for the propagation and reflection of the pulse wave. In-vivo cfPWV measurements from 57 subjects and numerical cfPWV data based on a one-dimensional model were used to assess the method and its performance was compared to three other existing approaches (waveform matching, intersecting tangent, and cross-correlation). The cfPWV calculated using the simplified tube-load model had better repeatability than the other methods (Intra-group Correlation Coefficient, ICC = 0.985). The model was also more accurate than other methods (deviation, 0.13 ms⁻¹) and was more robust when dealing with noisy signals. We conclude that the determination of cfPWV based on the proposed model can accurately and robustly evaluate arterial stiffness.

Predictive Ability of Pressure-Corrected Arterial Stiffness Indices: Comparison of Pulse Wave Velocity, Cardio-Ankle Vascular Index (CAVI), and CAVI0

BACKGROUND

Pulse wave velocity (PWV) is blood pressure (BP) dependent, leading to the development of the BP-corrected metrics cardio-ankle vascular index (CAVI) and CAVI0. We aimed to assess risk prediction by heart-to-ankle PWV (haPWV), CAVI, and CAVI0 in a US population.

METHODS

We included 154 subjects (94.8% male; 47.7% African American) with and without heart failure (HF). Left and right haPWV, CAVI, and CAVI0 were measured with the VaSera 1500N device. We prospectively followed participants for a mean of 2.56 years for the composite endpoint death or HF-related hospital admission (DHFA).

RESULTS

Left and right haPWV, CAVI, and CAVI0 values did not differ significantly. In unadjusted analyses, haPWV (left standardized hazard ratio [HR] = 1.51, P = 0.007; right HR = 1.66, P = 0.003), CAVI (left HR = 1.45, P = 0.012; right HR = 1.58, P = 0.006), and CAVI0 (left HR = 1.39, P = 0.022; right HR = 1.44, P = 0.014) significantly predicted DHFA. Predictive ability showed a decreasing trend from haPWV to CAVI to CAVI0; in line with the increasing amount of BP correction in these metrics. In Cox models, right-sided metrics showed a trend toward stronger predictive ability than left-sided metrics. After adjustment for baseline HF status, the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score, and systolic BP, right haPWV (HR = 1.58, P = 0.025) and CAVI (HR = 1.44, P = 0.044), but no other stiffness metrics, remained predictive.

CONCLUSIONS

Although conceptually attractive, BP-corrected arterial stiffness metrics do not offer better prediction of DHFA than conventional arterial stiffness metrics, nor do they predict DHFA independently of systolic BP. Our findings support PWV as the primary arterial stiffness metric for outcome prediction.

Using noninvasive adjusted pulse transit time for tracking beat-to-beat systolic blood pressure during ventricular arrhythmia

Tracking beat-to-beat blood pressure noninvasively during ventricular arrhythmia (VA) is of great importance but rarely reported. The goal of our study was to investigate the potential utility of the adjusted pulse transit time (APTT) to track beat-to-beat femoral systolic blood pressure (SBP) during VA. Patients who underwent radiofrequency ablation for arrhythmias at Fuwai Hospital were enrolled. Electrocardiograms (ECGs), finger photoplethysmograms, and femoral arterial blood pressure were recorded simultaneously during VA. The APTT was calculated as the ratio between the square of the conventional pulse transit time (cPTT) and the RR interval of the ECG waveform. Forty-five patients were enrolled in our study, and 22,849 beats were collected during their VA. The inverse of the APTT showed a good correlation with femoral SBP during VA (r = 0.70 ± 0.18). The APTT-derived SBP demonstrated acceptable accuracy in terms of the mean difference ± standard deviation (-0.01 ± 10.54 mmHg) from the invasive femoral SBP. The area under the receiver operating characteristic (ROC) curve for the ability of the APTT to detect ≥30% decreases in femoral SBP was 0.903 (95% confidential interval, 0.895-0.911). In addition, the APTT performed better than the cPTT and RR interval in the above analysis (all P < 0.05). Therefore, the APTT has acceptable accuracy in tracking beat-to-beat femoral SBP and could detect substantially decreased femoral SBP. These findings indicate that the APTT may be a promising noninvasive surrogate for invasive femoral SBP during VA. A multiparameter model combining APTT and other parameters is needed to further improve the accuracy.

Noninvasive Continuous Blood Pressure Estimation from Pulse Transit Time: A review of the calibration models

Noninvasive continuous blood pressure estimation is a promising alternative to minimally invasive blood pressure measurement using cuff and invasive catheter measurement, because it opens the way to both long-term and continuous blood pressure monitoring in ecological situation. The most current estimation algorithm is based on pulse transit time measurement where at least two measured signals need to be acquired. From the pulse transit time values, it is possible to estimate the continuous blood pressure for each cardiac cycle. This measurement highly depends on arterial properties which are not easily accessible with common measurement techniques; but these properties are needed as input for the estimation algorithm. With every change of input arterial properties, the error in the blood pressure estimation rises, thus a periodic calibration procedure is needed for error minimization. Recent research is focused on simplified constant arterial properties which are not constant over time and uses only linear model based on initial measurement. The elaboration of continuous calibration procedures, independent of recalibration measurement, is the key to improving the accuracy and robustness of noninvasive continuous blood pressure estimation. However, most models in literature are based on linear approximation and we discuss here the need for more complete calibration models.

Measurement of pulse transit time using ultra-wideband radar

BACKGROUND: The pulse transit time is an important factor that can be used to estimate the blood pressure indirectly. In many studies, pressures in the artery near and far from the heart are measured or the electrocardiogram and photoplethysmography are used to calculate the pulse transit time. In other words, the so-called contact measurements have been mainly used in these studies. OBJECTIVE: In this paper, a new method based on radar technology to measure the pulse transit time in a non-contact manner is proposed. METHODS: Radar pulses were simultaneously emitted to the chest and the wrist, and the reflected pulses were accumulated. Heartbeats were extracted by performing principal component analysis on each time series belonging to the accumulated pulses. Then, the matched heartbeat pairs were found among the heartbeats obtained from the chest and wrist and the time delay between them, i.e. the pulse transit time, was obtained. RESULTS: By comparing the pulse transit times obtained by the proposed method with those obtained by conventional methods, it is confirmed that the proposed method using the radar can be used to obtain the pulse transit time in a non-contact manner.

The impact of heart rate on pulse wave velocity: an in-silico evaluation

BACKGROUND

Clinical and experimental evidence regarding the influence of heart rate (HR) on arterial stiffness and its surrogate marker carotid-to-femoral pulse wave velocity (cf-PWV) is conflicting. We aimed to evaluate the effect of HR on cf-PWV measurement under controlled haemodynamic conditions and especially with respect to blood pressure (BP) that is a strong determinant of arterial stiffness.

METHOD

Fifty-nine simulated cases were created using a previously validated in-silico model. For each case, cf-PWV was measured at five HR values, 60, 70, 80, 90, 100 bpm. With increasing HR, we assessed cf-PWV under two scenarios: with BP free to vary in response to HR increase, and with aortic DBP (aoDBP) fixed to its baseline value at 60 bpm, by modifying total peripheral resistance accordingly. Further, we quantified the importance of arterial compliance (C) on cf-PWV changes caused by increasing HR.

RESULTS

When BP was left free to vary with HR, a significant HR-effect on cf-PWV (0.66 ± 0.24 m/s per 10 bpm, P < 0.001) was observed. This effect was reduced to 0.21 ± 0.14 m/s per 10 bpm (P = 0.048) when aoDBP was maintained fixed with increasing HR. The HR-effect on the BP-corrected cf-PWV was higher in the case of low C = 0.8 ± 0.3 ml/mmHg (0.26 ± 0.15 m/s per 10 bpm, P = 0.014) than the case of higher C = 1.7 ± 0.5 ml/mmHg (0.16 ± 0.07 m/s per 10 bpm, P = 0.045).

CONCLUSION

Our findings demonstrated that relatively small HR changes may only slightly affect the cf-PWV. Nevertheless, in cases wherein HR might vary at a greater extent, a more clinically significant impact on cf-PWV should be considered.

Heart rate and blood pressure dependence of aortic distensibility in rats: comparison of measured and calculated pulse wave velocity

OBJECTIVES

When assessing arterial stiffness, heart rate (HR) and blood pressure (BP) are potential confounders. It appears that the HR/BP dependences of pulse wave velocity (PWV) and distensibility are different, even though both assess arterial stiffness. This study aims to compare aortic PWV as measured using pulse transit time (PWVTT) and as calculated from distensibility (PWVdist) at the same measurement site and propose a solution to the disparity in dependences of PWVTT and PWVdist.

METHODS

Adult anaesthetized rats (n = 24) were randomly paced at HRs 300-500 bpm, at 50 bpm steps. At each step, aortic PWVTT (two pressure-tip catheters) and PWVdist (pressure-tip catheter and ultrasound wall-tracking; abdominal aorta) were measured simultaneously while BP was varied pharmacologically.

RESULTS

HR dependence of PWVdist paradoxically decreased at higher levels of BP. In addition, BP dependence of PWVdist was much larger than that of PWVTT. These discrepancies are explained in that standard PWVdist uses an approximate derivative of pressure to diameter, which overestimates PWV with increasing pulse pressure (PP). In vivo, PP decreases as HR increases, potentially causing a PWVdist decrease with HR. Estimating the full pressure-diameter curve for each HR corrected for this effect by enabling calculation of the true derivative at diastolic BP. This correction yielded a PWVdist that shows HR and BP dependences similar to those of PWVTT. As expected, BP dependence of all PWV metrics was much larger than HR dependence.

CONCLUSION

Measured and calculated PWV have different dependences on HR and BP. These differences are, at least in part, because of approximations made in using systolic and diastolic values to calculate distensibility.

Conventional pulse transit times as markers of blood pressure changes in humans

Pulse transit time (PTT) represents a potential approach for cuff-less blood pressure (BP) monitoring. Conventionally, PTT is determined by (1) measuring (a) ECG and ear, finger, or toe PPG waveforms or (b) two of these PPG waveforms and (2) detecting the time delay between the waveforms. The conventional PTTs (cPTTs) were compared in terms of correlation with BP in humans. Thirty-two volunteers [50% female; 52 (17) (mean (SD)) years; 25% hypertensive] were studied. The four waveforms and manual cuff BP were recorded before and after slow breathing, mental arithmetic, cold pressor, and sublingual nitroglycerin. Six cPTTs were detected as the time delays between the ECG R-wave and ear PPG foot, R-wave and finger PPG foot [finger pulse arrival time (PAT)], R-wave and toe PPG foot (toe PAT), ear and finger PPG feet, ear and toe PPG feet, and finger and toe PPG feet. These time delays were also detected via PPG peaks. The best correlation by a substantial extent was between toe PAT via the PPG foot and systolic BP [- 0.63 ± 0.05 (mean ± SE); p < 0.001 via one-way ANOVA]. Toe PAT is superior to other cPTTs including the popular finger PAT as a marker of changes in BP and systolic BP in particular.

Pulse transit time based respiratory rate estimation with singular spectrum analysis

Respiratory rate (RR) is an important vital sign which can be difficult to measure accurately and unobtrusively in routine clinical practice. Pulse transit time (PTT), on the other hand, is unobtrusive to collect from electrocardiogram (ECG) and photoplethysmogram (PPG) signals. Using PTT is a novel method to estimate and monitor blood pressure (BP) and RR. This study aimed to estimate continuous RR using PTT with singular spectrum analysis to extract respiratory components. The performance of this method was validated on 17 subjects who carried out spontaneous breathing and controlled deep breathing conditions. Three types of estimated RR parameters (average RR by power spectral density (PSD) (RR_PSD), number of breaths (RR_#), and instantaneous RR (RR_inst)) were compared with the corresponding reference RR. The reference RR was collected using a respiratory belt. Our findings demonstrate that the PTT signal reliably tracked respiratory variation with a root mean square error of 0.84, 1.11, and 0.74 breaths/min for RR_PSD, RR_#, and RR_inst estimations, respectively. Overall, RR estimated by PTT was more accurate than heart/pulse rate interval, QRS area, and PPG amplitude, which were also extracted from ECG and PPG. The results suggest that it may be feasible to use PTT as an estimation of RR and that ECG and PPG may be relied upon for monitoring not only RR but also BP and heart rate. Graphical abstract The Pulse Transit Time (PTT) based Respiratory Rate (RR) estimation with Singular Spectrum Analysis (SSA) provides a superior performance than the method with other respiratory indicators extracted from Electrocardiogram (ECG) or Photoplethysmogram (PPG).

A review on low-dimensional physics-based models of systemic arteries: application to estimation of central aortic pressure

The physiological processes and mechanisms of an arterial system are complex and subtle. Physics-based models have been proven to be a very useful tool to simulate actual physiological behavior of the arteries. The current physics-based models include high-dimensional models (2D and 3D models) and low-dimensional models (0D, 1D and tube-load models). High-dimensional models can describe the local hemodynamic information of arteries in detail. With regard to an exact model of the whole arterial system, a high-dimensional model is computationally impracticable since the complex geometry, viscosity or elastic properties and complex vectorial output need to be provided. For low-dimensional models, the structure, centerline and viscosity or elastic properties only need to be provided. Therefore, low-dimensional modeling with lower computational costs might be a more applicable approach to represent hemodynamic properties of the entire arterial system and these three types of low-dimensional models have been extensively used in the study of cardiovascular dynamics. In recent decades, application of physics-based models to estimate central aortic pressure has attracted increasing interest. However, to our best knowledge, there has been few review paper about reconstruction of central aortic pressure using these physics-based models. In this paper, three types of low-dimensional physical models (0D, 1D and tube-load models) of systemic arteries are reviewed, the application of three types of models on estimation of central aortic pressure is taken as an example to discuss their advantages and disadvantages, and the proper choice of models for specific researches and applications are advised.

Comment on 'New photoplethysmogram indicators for improving cuffless and continuous blood pressure estimation accuracy'

OBJECTIVE

A recent study investigated the potential utility of new photoplethysmogram (PPG) indicators to improve cuffless continuous blood pressure (BP) measurement.

APPROACH

In this Comment we provide additional discussion of the physiology underlying PPG- and pulse arrival time (PAT)-based BP measurement. We also discuss validation of these measurements.

MAIN RESULTS

Changes in PPG features and PAT can occur independently of BP. Any study validating BP measurement based on PPG features or PAT should include a variety of calibration independent physiological challenges affecting BP.

SIGNIFICANCE

PPG/PAT-based BP measurement has been investigated extensively as an alternative to cuff-based BP measurement. We feel the inherent physiological confounding in PPG/PAT-based measurement makes it unlikely that it will be of clinical value.

Monitoring the Relative Blood Pressure Using a Hydraulic Bed Sensor System

We propose a nonwearable hydraulic bed sensor system that is placed underneath the mattress to estimate the relative systolic blood pressure of a subject, which only differs from the actual blood pressure by a scaling and an offset factor. Two types of features are proposed to obtain the relative blood pressure, one based on the strength and the other on the morphology of the bed sensor ballistocardiogram pulses. The relative blood pressure is related to the actual by a scale and an offset factor that can be obtained through calibration. The proposed system is able to extract the relative blood pressure more accurately with a less sophisticated sensor system compared to those from the literature. We tested the system using a dataset collected from 48 subjects right after active exercises. Comparison with the ground truth obtained from the blood pressure cuff validates the promising performance of the proposed system, where the mean correlation between the estimate and the ground truth is near to 90% for the strength feature and 83% for the morphology feature.

Reconstruction of continuous brachial artery pressure wave from continuous finger arterial pressure in humans

Generalized transfer functions (GTFs) are available to compute the more relevant proximal blood pressure (BP) waveform from a more easily measured peripheral BP waveform. However, GTFs are based on the black box model. This paper presents a practical approach to reconstruct brachial artery pressure (BAP) distally from finger artery pressure (FAP). We assume that continuous BAP can be simply approximated by summing two halves of the continuous FAP shifted by the time delay. We firstly showed that the pressure wave in the finger artery can be considered twice as much as the forward/backward wave in the finger. A simplified individualized transfer function was then derived so as to estimate BAP from FAP. The effectiveness of the method was examined by experiment involving 26 healthy volunteers (26.7 ± 3.8 years old) in a resting state. By comparing with a reference BAP, we found that the proposed method can correct the FAP. The errors of the proposed method in estimating systolic and diastolic pressures are - 0.6 ± 6.0 and - 0.6 ± 3.7 mmHg, respectively. These results agree with the standard of Association for the Advancement of Medical Instrumentation (AAMI). We also found that the reconstructed BAP from FAP by terminal arterial occlusion technology (TAOT) is comparable to that of the artery occlusion technology (AOT). Our method or TAOT is promising in estimating continuous proximal blood pressure from peripheral blood pressure in practice.

Prognostic Utility of Morning Blood Pressure Surge for 20-Year All-Cause and Cardiovascular Mortalities: Results of a Community-Based Study

Background

Morning blood pressure (BP) surge (MS), defined by the MS amplitude, is an independent prognostic factor of cardiovascular outcomes in some, but not all, populations.

Method and Results

We enrolled 2020 participants (1029 men; aged 30–79 years) with 24‐hour ambulatory BP data. During a median 19.7‐year follow‐up, 607 deaths (182 by cardiovascular causes) were confirmed from the National Death Registry. The amplitude of sleep‐trough MS (STMS) was derived from the difference between morning systolic BP (SBP) and lowest nighttime SBP. The rate of STMS was derived as the slope of linear regression of sequential SBP measures on time intervals within the STMS period. Thresholds for high STMS amplitude and rate were determined by the 95th percentiles (43.7 mm Hg and 11.3 mm Hg/h, respectively). Multivariable Cox models, adjusting for age, sex, body mass index, smoking, alcohol, low‐density lipoprotein cholesterol, 24‐hour SBP, night:day SBP ratio, and antihypertensive treatment, revealed that a high STMS rate (hazard ratio, 1.666; 95% confidence interval, 1.185–2.341), but not STMS amplitude (hazard ratio, 1.245; 95% confidence interval, 0.984–1.843), was significantly associated with a greater mortality risk. Similarly, STMS rate (hazard ratio, 2.608; 95% confidence interval, 1.554–4.375), but not STMS amplitude, was significantly associated with the risk of cardiovascular mortality (hazard ratio, 0.966; 95% confidence interval, 0.535–1.747). Moreover, the prognostic values of STMS rate were comparable in subjects with or without morning and nocturnal hypertension (P>0.05 for interaction for all). In simulation studies, STMS rate was less susceptible to measurement errors of the sleep‐trough SBP than STMS amplitude.

Conclusions

STMS rate could independently help identify subjects with an increased cardiovascular risk.

Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Predictions on Maximum Calibration Period and Acceptable Error Limits

OBJECTIVE

Pulse transit time (PTT) is being widely pursued for ubiquitous blood pressure (BP) monitoring. PTT-based systems may require periodic cuff calibrations but can still be useful for hypertension screening by affording numerous out-of-clinic measurements that can be averaged. The objective was to predict the maximum calibration period that would not compromise accuracy and acceptable error limits in light of measurement averaging for PTT-based systems.

METHODS

Well-known mathematical models and vast BP data were leveraged. Models relating PTT, age, and gender to BP were employed to determine the maximum time period for the PTT-BP calibration curve to change by <1 mmHg over physiological BP ranges for each age and gender. A model of within-person BP variability was employed to establish the screening accuracy of the conventional cuff-based approach. These models were integrated to investigate the screening accuracy of the average of numerous measurements of a PTT-based system in relation to the accuracy of its individual measurements.

RESULTS

The maximum calibration period was about 1 year for a 30 year old and declined linearly to about 6 months for a 70 year old. A PTT-based system with a precision error of >12 mmHg for systolic BP could achieve the screening accuracy of the cuff-based approach via measurement averaging.

CONCLUSION

This theoretical study indicates that PTT-based BP monitoring is viable even with periodic calibration and seemingly high measurement errors.

SIGNIFICANCE

The predictions may help guide the implementation, evaluation, and application of PTT-based BP monitoring systems in practice.

Options for Dealing with Pressure Dependence of Pulse Wave Velocity as a Measure of Arterial Stiffness: An Update of Cardio-Ankle Vascular Index (CAVI) and CAVI0

Pulse wave velocity (PWV), a marker of arterial stiffness, is known to change instantaneously with changes in blood pressure. In this mini-review, we discuss two main approaches for handling the blood pressure dependence of PWV: (1) converting PWV into a pressure-independent index, and (2) correcting PWV per se for the pressure dependence. Under option 1, we focus on cardio-ankle vascular index (CAVI). CAVI is essentially a form of stiffness index β - CAVI is estimated for a (heart-to-ankle) trajectory, whereas β is estimated for a single artery from pressure and diameter measurements. Stiffness index β, and therefore also CAVI, have been shown to theoretically exhibit a slight residual blood pressure dependence due to the use of diastolic blood pressure instead of a fixed reference blood pressure. Additionally, CAVI exhibits pressure dependence due to the use of an estimated derivative of the pressure-diameter relationship. In this mini-review, we will address CAVI's blood pressure dependence theoretically, but also statistically. Furthermore, we review corrected indices (CAVI₀ and β₀) that theoretically do not show a residual blood pressure dependence. Under option 2, three ways of correcting PWV are reviewed: (1) using an exponential relationship between pressure and cross-sectional area, (2) by statistical model adjustment, and (3) through reference values or rule of thumb. Method 2 requires a population to be studied to characterise the statistical model, and method 3 requires a representative reference study. Given these limitations, method 1 seems preferable for correcting PWV per se for its blood pressure dependence. In summary, several options are available to handle the blood pressure dependence of PWV. If a blood pressure-independent index is sought, CAVI₀ is theoretically preferable over CAVI. If correcting PWV per se is required, using an exponential pressure-area relationship provides the user with a method to correct PWV on an individual basis.

Weighing Scale-Based Pulse Transit Time is a Superior Marker of Blood Pressure than Conventional Pulse Arrival Time

Pulse transit time (PTT) is being widely pursued for cuff-less blood pressure (BP) monitoring. Most efforts have employed the time delay between ECG and finger photoplethysmography (PPG) waveforms as a convenient surrogate of PTT. However, these conventional pulse arrival time (PAT) measurements include the pre-ejection period (PEP) and the time delay through small, muscular arteries and may thus be an unreliable marker of BP. We assessed a bathroom weighing scale-like system for convenient measurement of ballistocardiography and foot PPG waveforms – and thus PTT through larger, more elastic arteries – in terms of its ability to improve tracking of BP in individual subjects. We measured “scale PTT”, conventional PAT, and cuff BP in humans during interventions that increased BP but changed PEP and smooth muscle contraction differently. Scale PTT tracked the diastolic BP changes well, with correlation coefficient of −0.80 ± 0.02 (mean ± SE) and root-mean-squared-error of 7.6 ± 0.5 mmHg after a best-case calibration. Conventional PAT was significantly inferior in tracking these changes, with correlation coefficient of −0.60 ± 0.04 and root-mean-squared-error of 14.6 ± 1.5 mmHg (p < 0.05). Scale PTT also tracked the systolic BP changes better than conventional PAT but not to an acceptable level. With further development, scale PTT may permit reliable, convenient measurement of BP.