Nonlinear Viscoelastic Modeling of Finger Arteries: Toward Smartphone-Based Blood Pressure Monitoring via the Oscillometric Finger Pressing Method.

OBJECTIVE: Oscillometric finger pressing is a smartphone-based blood pressure (BP) monitoring method. Finger photoplethysmography (PPG) oscillations and pressure are measured during a steady increase in finger pressure, and an algorithm computes systolic BP (SP) and diastolic BP (DP) from the measurements. The objective was to assess the impact of finger artery viscoelasticity on the BP computation. METHODS: Nonlinear viscoelastic models relating transmural pressure (finger BP - applied pressure) to PPG oscillations during finger pressing were developed. The output of each model to a measured transmural pressure input was fitted to measured PPG oscillations from 15 participants. A parametric sensitivity analysis was performed via model simulations to elucidate the viscoelastic effect on the derivative-based BP computation algorithm. RESULTS: A Wiener viscoelastic model comprising a first-order transfer function followed by a static sigmoidal function fitted the measured PPG oscillations better than an elastic model containing only the static function (median (IQR) error of 30.5% (25.6%-34.0%) vs 50.9% (46.7%-53.7%); p<0.01). In Wiener model simulations, the derivative algorithm underestimated SP, especially with high pulse pressure and low transfer function cutoff frequency (i.e., greater viscoelasticity). The mean of the normalized PPG waveform at the maximum oscillation beat was found to correlate with the cutoff frequency (r = -0.8) and could thus possibly be used to compensate for viscoelasticity. CONCLUSION: Finger artery viscoelasticity negatively impacts oscillometric BP computation algorithms but can potentially be compensated for using available measurements. SIGNIFICANCE: These findings may help in converting smartphones into truly cuffless BP monitors for improving hypertension awareness and control.

Peripheral artery disease diagnosis based on deep learning-enabled analysis of non-invasive arterial pulse waveforms.

This paper intends to investigate the feasibility of peripheral artery disease (PAD) diagnosis based on the analysis of non-invasive arterial pulse waveforms. We generated realistic synthetic arterial blood pressure (BP) and pulse volume recording (PVR) waveform signals pertaining to PAD present at the abdominal aorta with a wide range of severity levels using a mathematical model that simulates arterial blood circulation and arterial BP-PVR relationships. We developed a deep learning (DL)-enabled algorithm that can diagnose PAD by analyzing brachial and tibial PVR waveforms, and evaluated its efficacy in comparison with the same DL-enabled algorithm based on brachial and tibial arterial BP waveforms as well as the ankle-brachial index (ABI). The results suggested that it is possible to detect PAD based on DL-enabled PVR waveform analysis with adequate accuracy, and its detection efficacy is close to when arterial BP is used (positive and negative predictive values at 40 % abdominal aorta occlusion: 0.78 vs 0.89 and 0.85 vs 0.94; area under the ROC curve (AUC): 0.90 vs 0.97). On the other hand, its efficacy in estimating PAD severity level is not as good as when arterial BP is used (r value: 0.77 vs 0.93; Bland-Altman limits of agreement: -32%-+32 % vs -20%-+19 %). In addition, DL-enabled PVR waveform analysis significantly outperformed ABI in both detection and severity estimation. In sum, the findings from this paper suggest the potential of DL-enabled non-invasive arterial pulse waveform analysis as an affordable and non-invasive means for PAD diagnosis.

A Physical Model-Based Approach to One-Point Calibration of Pulse Transit Time to Blood Pressure.

OBJECTIVE: To develop a novel physical model-based approach to enable 1-point calibration of pulse transit time (PTT) to blood pressure (BP). METHODS: The proposed PTT-BP calibration model is derived by combining the Bramwell-Hill equation and a phenomenological model of the arterial compliance (AC) curve. By imposing a physiologically plausible constraint on the skewness of AC at positive and negative transmural pressures, the number of tunable parameters in the PTT-BP calibration model reduces to 1. Hence, as opposed to most existing PTT-BP calibration models requiring multiple (≥2) PTT-BP measurements to personalize, the PTT-BP calibration model can be personalized to an individual subject using a single PTT-BP measurement pair. Equipped with the physically relevant PTT-AC and AC-BP relationships, the proposed approach may serve as a universal means to calibrate PTT to BP over a wide BP range. The validity and proof-of-concept of the proposed approach were evaluated using PTT and BP measurements collected from 22 healthy young volunteers undergoing large BP changes. RESULTS: The proposed approach modestly yet significantly outperformed an empiric linear PTT-BP calibration with a group-average slope and subject-specific intercept in terms of bias (5.5 mmHg vs 6.4 mmHg), precision (8.4 mmHg vs 9.4 mmHg), mean absolute error (7.8 mmHg vs 8.8 mmHg), and root-mean-squared error (8.7 mmHg vs 10.3 mmHg, all in the case of diastolic BP). CONCLUSION: We demonstrated the preliminary proof-of-concept of an innovative physical model-based approach to one-point PTT-BP calibration. SIGNIFICANCE: The proposed physical model-based approach has the potential to enable more accurate and convenient calibration of PTT to BP.

Cardiovascular variability, sociodemographics, and biomarkers of disease: the MIDUS study.

Introduction: Like heart rate, blood pressure (BP) is not steady but varies over intervals as long as months to as short as consecutive cardiac cycles. This blood pressure variability (BPV) consists of regularly occurring oscillations as well as less well-organized changes and typically is computed as the standard deviation of multiple clinic visit-to-visit (VVV-BP) measures or from 24-h ambulatory BP recordings (ABPV). BP also varies on a beat-to-beat basis, quantified by methods that parse variation into discrete bins, e.g., low frequency (0.04-0.15 Hz, LF). However, beat-to-beat BPV requires continuous recordings that are not easily acquired. As a result, we know little about the relationship between LF-BPV and basic sociodemographic characteristics such as age, sex, and race and clinical conditions. Methods: We computed LF-BPV during an 11-min resting period in 2,118 participants in the Midlife in the US (MIDUS) study. Results: LF-BPV was negatively associated with age, greater in men than women, and unrelated to race or socioeconomic status. It was greater in participants with hypertension but unrelated to hyperlipidemia, hypertriglyceridemia, diabetes, elevated CRP, or obesity. LF-diastolic BPV (DBPV), but not-systolic BPV (SBPV), was negatively correlated with IL-6 and s-ICAM and positively correlated with urinary epinephrine and cortisol. Finally, LF-DBPV was negatively associated with mortality, an effect was rendered nonsignificant by adjustment by age but not other sociodemographic characteristics. Discussion: These findings, the first from a large, national sample, suggest that LF-BPV differs significantly from VVV-BP and ABPV. Confirming its relationship to sociodemographic risk factors and clinical outcomes requires further study with large and representative samples.

Current evidence suggests that estimating blood pressure from convenient ECG waveforms alone is not viable.

Cuffless blood pressure (BP) measurement could improve hypertension awareness and control and is being widely pursued. Some have proposed to estimate BP from the electrocardiogram (ECG) alone despite little physiological basis. In this minireview, we extracted the most relevant articles related to ECG-based BP estimation. Our findings suggest that, as expected, estimating BP from ECG does not appear to be viable. Most notably, we have not found any evidence that ECG features can track BP changes. At best, certain ECG features may indicate heart disease and thus correlate with high BP, but this may not be clinically useful.

The 2023 wearable photoplethysmography roadmap.

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.

European Society of Hypertension recommendations for the validation of cuffless blood pressure measuring devices: European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability.

BACKGROUND: There is intense effort to develop cuffless blood pressure (BP) measuring devices, and several are already on the market claiming that they provide accurate measurements. These devices are heterogeneous in measurement principle, intended use, functions, and calibration, and have special accuracy issues requiring different validation than classic cuff BP monitors. To date, there are no generally accepted protocols for their validation to ensure adequate accuracy for clinical use. OBJECTIVE: This statement by the European Society of Hypertension (ESH) Working Group on BP Monitoring and Cardiovascular Variability recommends procedures for validating intermittent cuffless BP devices (providing measurements every >30 sec and usually 30-60 min, or upon user initiation), which are most common. VALIDATION PROCEDURES: Six validation tests are defined for evaluating different aspects of intermittent cuffless devices: static test (absolute BP accuracy); device position test (hydrostatic pressure effect robustness); treatment test (BP decrease accuracy); awake/asleep test (BP change accuracy); exercise test (BP increase accuracy); and recalibration test (cuff calibration stability over time). Not all these tests are required for a given device. The necessary tests depend on whether the device requires individual user calibration, measures automatically or manually, and takes measurements in more than one position. CONCLUSION: The validation of cuffless BP devices is complex and needs to be tailored according to their functions and calibration. These ESH recommendations present specific, clinically meaningful, and pragmatic validation procedures for different types of intermittent cuffless devices to ensure that only accurate devices will be used in the evaluation and management of hypertension.

Smartphone-Based Blood Pressure Monitoring via the Oscillometric Finger Pressing Method: Analysis of Oscillation Width Variations Can Improve Diastolic Pressure Computation.

OBJECTIVE: Oscillometric finger pressing is a potential method for absolute blood pressure (BP) monitoring via a smartphone. The user presses their fingertip against a photoplethysmography-force sensor unit on a smartphone to steadily increase the external pressure on the underlying artery. Meanwhile, the phone guides the finger pressing and computes systolic BP (SP) and diastolic BP (DP) from the measured blood volume oscillations and finger pressure. The objective was to develop and evaluate reliable finger oscillometric BP computation algorithms. METHODS: The collapsibility of thin finger arteries was exploited in an oscillometric model to develop simple algorithms for computing BP from the finger pressing measurements. These algorithms extract features from "width" oscillograms (oscillation width versus finger pressure functions) and the conventional "height" oscillogram for markers of DP and SP. Finger pressing measurements were obtained using a custom system along with reference arm cuff BP measurements from 22 subjects. Measurements were also obtained during BP interventions in some subjects for 34 total measurements. RESULTS: An algorithm employing the average of width and height oscillogram features predicted DP with correlation of 0.86 and precision error of 8.6 mmHg with respect to the reference measurements. Analysis of arm oscillometric cuff pressure waveforms from an existing patient database provided evidence that the width oscillogram features are better suited to finger oscillometry. CONCLUSION: Analysis of oscillation width variations during finger pressing can improve DP computation. SIGNIFICANCE: The study findings may help in converting widely available devices into truly cuffless BP monitors for improving hypertension awareness and control.

Toward Real-Time Blood Pressure Monitoring via High-Fidelity Iontronic Tonometric Sensors with High Sensitivity and Large Dynamic Ranges.

Continuous, noninvasive blood pressure (CNIBP) monitoring provides valuable hemodynamic information that renders detection of the early onset of cardiovascular diseases. Wearable mechano-electric pressure sensors that mount on the skin are promising candidates for monitoring continuous blood pressure (BP) pulse waveforms due to their excellent conformability, simple sensing mechanisms, and convenient signal acquisition. However, it is challenging to acquire high-fidelity BP pulse waveforms since it requires highly sensitive sensors (sensitivity larger than 4 × 10-5 kPa-1 ) that respond linearly with pressure change over a large dynamic range, covering the typical BP range (5-25 kPa). Herein, this work introduces a high-fidelity, iontronic-based tonometric sensor (ITS) with high sensitivity (4.82 kPa-1 ), good linearity (R2 > 0.995), and a large dynamic range (up to 180% output change) over a broad working range (0 to 38 kPa). Additionally, the ITS demonstrates a low limit of detection at 40 Pa, a fast load response time (35 ms) and release time (35 ms), as well as a stable response over 5000 load per release cycles, paving ways for potential applications in human-interface interaction, electronic skins, and robotic haptics. This work further explores the application of the ITS in monitoring real-time, beat-to-beat BP by measuring the brachial and radial pulse waveforms. This work provides a rational design of a wearable pressure sensor with high sensitivity, good linearity, and a large dynamic range for real-time CNIBP monitoring.

The Microsoft Research Aurora Project: Important Findings on Cuffless Blood Pressure Measurement.

Conventional blood pressure (BP) measurement devices based on an inflatable cuff only provide a narrow view of the continuous BP profile. Cuffless BP measuring technologies could permit numerous BP readings throughout daily life and thereby considerably improve the assessment and management of hypertension. Several wearable cuffless BP devices based on pulse wave analysis (applied to a photoplethysmography or tonometry waveform) with or without use of pulse arrival time are now available on the market. The key question is: Can these devices provide accurate measurement of BP? Microsoft Research recently published a complex article describing perhaps the most important and highest resource project to date (Aurora Project) on assessing the accuracy of several pulse wave analysis and pulse wave analysis-pulse arrival time devices. The overall results from 1125 participants were clear-cut negative. The present article motivates and describes emerging cuffless BP devices and then summarizes the Aurora Project. The study methodology and findings are next discussed in the context of regulatory-cleared devices, physiology, and related studies, and the study strengths and limitations are pinpointed thereafter. Finally, the implications of the Aurora Project are briefly stated and recommendations for future work are offered to finally realize the considerable potential of cuffless BP measurement in health care.

Mathematical Modeling of Oscillometric Blood Pressure Measurement: A Complete, Reduced Oscillogram Model.

OBJECTIVE: Oscillogram modeling is a powerful tool for understanding and advancing popular oscillometric blood pressure (BP) measurement. A reduced oscillogram model relating cuff pressure oscillation amplitude ( ∆O) to external cuff pressure of the artery ( Pe) is: [Formula: see text], where g(P) is the arterial compliance versus transmural pressure ( P) curve, Ps and Pd are systolic and diastolic BP, and k is the reciprocal of the cuff compliance. The objective was to determine an optimal functional form for the arterial compliance curve. METHODS: Eight prospective, three-parameter functions of the brachial artery compliance curve were compared. The study data included oscillometric arm cuff pressure waveforms and invasive brachial BP from 122 patients covering a 20-120 mmHg pulse pressure range. The oscillogram measurements were constructed from the cuff pressure waveforms. Reduced oscillogram models, inputted with measured systolic and diastolic BP and each parametric brachial artery compliance curve function, were optimally fitted to the oscillogram measurements in the least squares sense. RESULTS: An exponential-linear function yielded as good or better model fits compared to the other functions, with errors of 7.9±0.3 and 5.1±0.2% for tail-trimmed and lower half-trimmed oscillogram measurements. Importantly, this function was also the most tractable mathematically. CONCLUSION: A three-parameter exponential-linear function is an optimal form for the arterial compliance curve in the reduced oscillogram model and may thus serve as the standard function for this model henceforth. SIGNIFICANCE: The complete, reduced oscillogram model determined herein can potentially improve oscillometric BP measurement accuracy while advancing foundational knowledge.

Abdominal aortic aneurysm monitoring via arterial waveform analysis: towards a convenient point-of-care device.

Abdominal aortic aneurysms (AAAs) are lethal but treatable yet substantially under-diagnosed and under-monitored. Hence, new AAA monitoring devices that are convenient in use and cost are needed. Our hypothesis is that analysis of arterial waveforms, which could be obtained with such a device, can provide information about AAA size. We aim to initially test this hypothesis via tonometric waveforms. We study noninvasive carotid and femoral blood pressure (BP) waveforms and reference image-based maximal aortic diameter measurements from 50 AAA patients as well as the two noninvasive BP waveforms from these patients after endovascular repair (EVAR) and from 50 comparable control patients. We develop linear regression models for predicting the maximal aortic diameter from waveform or non-waveform features. We evaluate the models in out-of-training data in terms of predicting the maximal aortic diameter value and changes induced by EVAR. The best model includes the carotid area ratio (diastolic area divided by systolic area) and normalized carotid-femoral pulse transit time ((age·diastolic BP)/(height/PTT)) as input features with positive model coefficients. This model is explainable based on the early, negative wave reflection in AAA and the Moens-Korteweg equation for relating PTT to vessel diameter. The predicted maximal aortic diameters yield receiver operating characteristic area under the curves of 0.83 ± 0.04 in classifying AAA versus control patients and 0.72 ± 0.04 in classifying AAA patients before versus after EVAR. These results are significantly better than a baseline model excluding waveform features as input. Our findings could potentially translate to convenient devices that serve as an adjunct to imaging.

Linear and nonlinear identification of the carotid sinus baroreflex in the very low-frequency range.

Since the arterial baroreflex system is classified as an immediate control system, the focus has been on analyzing its dynamic characteristics in the frequency range between 0.01 and 1 Hz. Although the dynamic characteristics in the frequency range below 0.01 Hz are not expected to be large, actual experimental data are scant. The aim was to identify the dynamic characteristics of the carotid sinus baroreflex in the frequency range down to 0.001 Hz. The carotid sinus baroreceptor regions were isolated from the systemic circulation, and carotid sinus pressure (CSP) was changed every 10 s according to Gaussian white noise with a mean of 120 mmHg and standard deviation of 20 mmHg for 90 min in anesthetized Wistar-Kyoto rats (n = 8). The dynamic gain of the linear transfer function relating CSP to arterial pressure (AP) at 0.001 Hz tended to be greater than that at 0.01 Hz (1.060 ± 0.197 vs. 0.625 ± 0.067, p = 0.080), suggesting that baroreflex control was largely maintained at 0.001 Hz. Regarding nonlinear analysis, a second-order Uryson model predicted AP with a higher R2 value (0.645 ± 0.053) than a linear model (R2  = 0.543 ± 0.057, p = 0.025) or a second-order Volterra model (R2  = 0.589 ± 0.055, p = 0.045) in testing data. These pieces of information may be used to create baroreflex models that can add a component of autonomic control to a cardiovascular digital twin for predicting acute hemodynamic responses to treatments and tailoring individual treatment strategies.

Cuffless blood pressure measuring devices: review and statement by the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability.

BACKGROUND: Many cuffless blood pressure (BP) measuring devices are currently on the market claiming that they provide accurate BP measurements. These technologies have considerable potential to improve the awareness, treatment, and management of hypertension. However, recent guidelines by the European Society of Hypertension do not recommend cuffless devices for the diagnosis and management of hypertension. OBJECTIVE: This statement by the European Society of Hypertension Working Group on BP Monitoring and Cardiovascular Variability presents the types of cuffless BP technologies, issues in their validation, and recommendations for clinical practice. STATEMENTS: Cuffless BP monitors constitute a wide and heterogeneous group of novel technologies and devices with different intended uses. Cuffless BP devices have specific accuracy issues, which render the established validation protocols for cuff BP devices inadequate for their validation. In 2014, the Institute of Electrical and Electronics Engineers published a standard for the validation of cuffless BP devices, and the International Organization for Standardization is currently developing another standard. The validation of cuffless devices should address issues related to the need of individual cuff calibration, the stability of measurements post calibration, the ability to track BP changes, and the implementation of machine learning technology. Clinical field investigations may also be considered and issues regarding the clinical implementation of cuffless BP readings should be investigated. CONCLUSION: Cuffless BP devices have considerable potential for changing the diagnosis and management of hypertension. However, fundamental questions regarding their accuracy, performance, and implementation need to be carefully addressed before they can be recommended for clinical use.

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.

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.

Simultaneous adaption of the gain and phase of a generalized transfer function for aortic pressure waveform estimation.

GOAL: This paper proposes and validates a completely adaptive transfer function (CATF) based on an autoregressive exogenous (ARX) model which adjusts the gain and phase of a generalized transfer function (GTF) simultaneously to estimate the aortic pressure waveform from a brachial pressure waveform. METHODS: Invasive aortic and brachial pressure waveforms were recorded from 34 subjects for the validation of the proposed method. Individual transfer functions (ITFs) were trained based on the pressure waveforms using an ARX model. The GTF was derived by averaging the ITFs. CATF was then obtained by adjusting both the gain and phase of the GTF using regression formulas calculated from the ITFs and brachial hemodynamic parameters. Meanwhile the quantitative contributions of the adaption of gain and phase of the GTF were investigated respectively. The root-mean-square-error of the total waveform and absolute errors of common hemodynamic indices including systolic and diastolic blood pressures (SBP and DBP, respectively), pulse pressure (PP) and augmentation index were used to evaluate the performance of the proposed method in the data divided into low, middle and high PP amplification groups. RESULTS: The CATF achieved lower errors for DBP and PP in the low PP amplification group (1.79 versus 2.10 mmHg and 5.08 versus 6.23 mmHg, respectively, both P < 0.05) and PP in the middle amplification group (1.43 versus 1.92 mmHg, P < 0.05) compared with the GTF. SIGNIFICANCE: The proposed method provides a step towards the development of an improved and clinically useful non-invasive approach for estimating the aortic pressure waveform from a peripheral pressure waveform.

Photoplethysmography Fast Upstroke Time Intervals Can Be Useful Features for Cuff-Less Measurement of Blood Pressure Changes in Humans.

OBJECTIVE: Photoplethysmography (PPG) waveform analysis is being increasingly investigated for continuous, non-invasive, and cuff-less blood pressure (BP) measurement. However, the efficacy of this approach and the useful features and models remain largely unclear. The objectives were to develop easy-to-understand models relating PPG waveform features to BP changes (after a cuff calibration) and to determine their value in BP measurement accuracy. METHODS: The study data comprised finger, toe, and ear PPG waveforms, an ECG waveform, and reference manual cuff BP measurements from 32 human subjects (25% hypertensive) before and after slow breathing, mental arithmetic, cold pressor, and nitroglycerin administration. Stepwise linear regression was employed to create parsimonious models for predicting the intervention-induced BP changes from popular PPG waveform features, pulse arrival time (PAT, time delay between ECG R-wave and PPG foot), and subject demographics. Leave-one-subject-out cross validation was applied to compare the BP change prediction root-mean-squared-errors (RMSEs) of the resulting models to reference models in which PPG waveform features were excluded. RESULTS: Finger b-time (PPG foot to minimum second derivative time interval) and ear "STT" (PPG amplitude divided by maximum derivative), when combined with PAT, reduced the systolic BP change prediction RMSE of reference models by 6-7% (p 0.022). Ear STT together with pulse width reduced the diastolic BP change prediction RMSE of the reference model by 13% (p = 0.003). CONCLUSION: The two PPG fast upstroke time intervals can offer some added value in cuff-less BP trending. SIGNIFICANCE: This study offers important information towards achieving non-invasive and passive BP monitoring without a cuff.

Posture-Dependent Variability in Wrist Ballistocardiogram-Photoplethysmogram Pulse Transit Time: Implication to Cuff-Less Blood Pressure Tracking.

OBJECTIVE: Toward the ultimate goal of robust cuff-less blood pressure (BP) tracking with wrist wearables against postural changes, the goal of this work was to investigate posture-dependent variability in pulse transit time (PTT) measured with ballistocardiogram (BCG) and photoplethysmogram (PPG) signal pair at the wrist. METHODS: BCG and PPG signals were acquired from 25 subjects under the combination of 3 body (standing, sitting, and supine) and 3 arm (vertical in head-to-foot direction, placed on the chest, and holding a shoulder) postures. PTT was computed as the time interval between the BCG J wave and the PPG foot, and the impact of the 9 postures on PTT was analyzed by invoking an array of possible physical mechanisms. RESULTS: Our work suggests that (i) wrist BCG-PPG PTT is consistent under standing and sitting postures with vertically held arms; and (ii) changes in wrist orientation and height as well as restrictions in body and arm movement may alter wrist BCG-PPG PTT via distortions in the wrist BCG and PPG waveforms. The results indicate that wrist BCG-PPG PTT varies with respect to postures even when BP remains constant. CONCLUSION: The potential of cuff-less BP tracking via wrist BCG-PPG PTT demonstrated under standing posture with arms vertically down in the head-to-foot direction may not generalize to other body and arm postures. SIGNIFICANCE: Understanding the physical mechanisms responsible for posture-induced BCG-PPG PTT variability may increase the versatility of the wrist BCG for cuff-less BP tracking.

Assessment of Calibration Models for Cuff-Less Blood Pressure Measurement After One Year of Aging.

OBJECTIVE: Many calibration models for cuff-less blood pressure (BP) measurement must be periodically updated with cuff BP values to account for vascular aging. However, the time period required for these "cuff re-calibrations" is largely unknown. The impact of one year of aging on several calibration models was assessed. METHODS: Ten humans (6 males, 57±18 years, 3 hypertensives) were studied during multiple recording sessions that occurred one year apart. In each session, electrocardiography (ECG), ear photoplethysmography (PPG), finger PPG, and toe PPG waveforms and manual cuff BP were recorded before and after slow breathing, mental arithmetic, cold pressor, and nitroglycerin. Linear models based on each PPG waveform, which were previously shown to offer value in predicting the intervention-induced BP changes in a larger subject cohort, were employed. The model coefficients were determined for each subject via one session, and the fully-defined, subject-specific calibration models were then evaluated in the corresponding subjects via the session one year later. RESULTS: Only a linear model relating toe pulse arrival time (PAT) - time delay between ECG R-wave and toe PPG foot - to systolic BP (SBP) remained useful. After the year, this model changed little on average (root-mean-squared-error (RMSE) = 1.5 mmHg) and predicted the cuff BP values better than the average of the initial cuff BP values of the subject (RMSE = 9.6±0.8 mmHg vs. 12.7±1.0 mmHg; p < 0.05). CONCLUSION: These results suggest annual cuff recalibrations for the toe PAT-SBP model. SIGNIFICANCE: Toe PAT may offer a practical recalibration period that fosters user adherence.