A smartphone application toward detection of systolic hypertension in underserved populations.

High systolic blood pressure (BP) is the most important modifiable risk factor for cardiovascular disease. Managing systolic hypertension is especially difficult in underserved populations wherein access to cuff BP devices is limited. We showed that ubiquitous smartphones without force sensing can be converted into absolute pulse pressure (PP) monitors. The concept is for the user to perform guided thumb and hand maneuvers with the phone to induce cuff-like actuation and allow built-in sensors to make cuff-like measurements for computing PP. We developed an Android smartphone PP application. The 'app' could be learned by volunteers and yielded PP with total error < 8 mmHg against cuff PP (N = 24). We also analyzed a large population-level database comprising adults less than 65 years old to show that PP plus other basic information can detect systolic hypertension with ROC AUC of 0.9. The smartphone PP app could ultimately help reduce the burden of systolic hypertension in underserved populations and thus health disparities.

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.

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.

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.

Month-long Respiratory Support by a Wearable Pumping Artificial Lung in an Ovine Model.

BACKGROUND: A wearable artificial lung could improve lung transplantation outcomes by easing implementation of physical rehabilitation during long-term pretransplant respiratory support. The Modular Extracorporeal Lung Assist System (ModELAS) is a compact pumping artificial lung currently under development. This study evaluated the long-term in vivo performance of the ModELAS during venovenous support in awake sheep. Feedback from early trials and computational fluid dynamic analysis guided device design optimization along the way. METHODS: The ModELAS was connected to healthy sheep via a dual-lumen cannula in the jugular vein. Sheep were housed in a fixed-tether pen while wearing the device in a holster during support. Targeted blood flow rate and support duration were 2-2.5 L/min and 28-30 days, respectively. Anticoagulation was maintained via systemic heparin. Device pumping and gas exchange performance and hematologic indicators of sheep physiology were measured throughout support. RESULTS: Computational fluid dynamic-guided design modifications successfully decreased pump thrombogenicity from initial designs. For the optimized design, 4 of 5 trials advancing past early perioperative and cannula-related complications lasted the full month of support. Blood flow rate and CO2 removal in these trials were 2.1 ± 0.3 L/min and 139 ± 15 mL/min, respectively, and were stable during support. One trial ended after 22 days of support due to intradevice thrombosis. Support was well tolerated by the sheep with no signs of hemolysis or device-related organ impairment. CONCLUSIONS: These results demonstrate the ability of the ModELAS to provide safe month-long support without consistent deterioration of pumping or gas exchange capabilities.