Accurate Blood Pressure Measurement Research Articles

Smartphone application-based intervention to lower blood pressure: a systematic review and meta-analysis.

Nowadays, the mHealth market is flooded with smartphone applications (apps) lacking validation for blood pressure (BP)-lowering effects and BP measurement accuracy. This systematic review for Guidelines for BP control using digital technologies of the Japanese Society of Hypertension aimed to assess the validation studies of apps. We searched eligible studies in Ovid MEDLINE, Cochrane Library, and Ichushi, focusing on randomized controlled trials and observational studies comparing the effects of smartphone app-based interventions with non-digital healthcare. Random effects models of meta-analysis were employed to estimate the pooled effects of mean BP change and 95% confidence intervals (CIs). Out of 7385 studies screened, 76 studies with 46,459 participants were included. The interventions were significantly associated with a reduction in office systolic and diastolic BP at six months (systolic BP, -2.76 mmHg, 95% CI: -3.94 to -1.58; diastolic BP, -1.23 mmHg, -1.80 to -0.67). Normotensives saw a significant reduction in office systolic BP at three-month (-4.44 mmHg, -6.96 to -1.92), diminishing afterward (six-month, 0.86 mmHg, -2.81 to 4.52; twelve-month, 0.86 mmHg, -2.81 to 4.52). Conversely, hypertensive participants experienced a significant reduction in office systolic BP at both three- and six-month (three-month, -7.71 mmHg, -10.63 to -4.79; six-month, -1.88 mmHg, -3.41 to -0.35), albeit with limited evidence thereafter. A larger BP reduction was observed among participants using apps with wireless transmission of BP measurements (P = 0.047 for interaction), while there was no clear difference in BP reduction according to the presence of other functions. Smartphone app-based interventions may hold the potential to improve BP levels.

Accurate and 30-plus days reliable cuffless blood pressure measurements with 9-minutes personal photoplethysmograph data and mixed deduction learning

Cuffless blood pressure (BP) measurements have long been anticipated, and the PPG (Photoplethysmography)-only method is the most promising one since already embedded in many wearable devices. To further meet the clinical accuracy requirements, PPG-only BP predictions with personalized modeling for overcoming personal deviations have been widely studied, but all required tens to hundreds of minutes of personal PPG measurements for training. Moreover, their accurate test periods without calibration practice were not reported. In this work, we collected records of PPG data from our recruited subjects in real-life scenarios instead of relying on the openly available MIMIC dataset obtained from intensive care unit (ICU) patients. Since our objective is commercial application and a substantial reduction in training data, we tailored our model training to closely mimic real-world usage. To achieve this, we developed a training approach that only requires 9-minutes of personal PPG signal recordings and mixed with other PPG data from our recruited 364 subjects. The modeling is conducted with two-channel paired inputs to the convolutional neural network (CNN)-based model, which we called Mixed Deduction Learning (MDL). The test results of 88 samples from 15 subjects, under testing period up to 30-plus days without extra calibration, revealed that MDL meets most of the standards of AAMI, BHS, and IEEE 1708–2014 (for static test only) for BP measurement devices, which indicates MDL’s long-term stability and consistency. Furthermore, we found that the model with two-channel inputs presents a trend of improving performance as the pool of mixed training data increased, while the conventional one-channel input revealed degraded performance. The outperformance of MDL is attributed to many significant features remained in the first CNN layer even when mixing personal 9-minutes data with the other 364 subjects. Consequently, PPG-only with MDL introduces a new avenue for overcoming challenges in training due to personal physiological variations. Given our consideration of real-life usage, this technology can be seamlessly translated to commercial applications.

Automated Digital Sfigmomanometer Prototype Testing

Abstract Blood pressure is the pressure of blood flow in the arteries generated by the heart. Abnormal blood pressure can lead to hypertension and hypotension. Hypotension, or low blood pressure, has a prevalence of 5% to 34% among individuals aged 17 to 19, and over 50% in the elderly. Hypertension can cause death in patients with heart disease. About 39.7% of people suffer from hypertension, especially those over the age of 60. Blood pressure measurement needs to be done regularly because it has impact such as early detection of blood pressure health conditions and monitoring of health conditions for those already diagnosed with abnormal blood pressure. Unfortunately, only 59% of the population in Indonesia regularly measure their blood pressure. Accurate blood pressure measurement can be performed using an invasive method. Another method is non-invasive, which can be done using a sphygmomanometer that applies the oscillometric method. This method uses pressure oscillations in the cuff influenced by the pulse in the blood vessels. When using this method, several factors need to be considered, such as body position, cuff size, and the technique used during the measurement. In this study, a fully automatic digital sphygmomanometer has been developed with a cuff attached to the device, equipped with a thermal printer to print out the measurement results and classify blood pressure categories. The advantage of the developed prototype is that it has a smaller relative error value, with 1.03% for systolic blood pressure and 1.45% for diastolic blood pressure, and has already been integrated with a thermal printer to directly print the measurement results.

BP-Diff: a conditional diffusion model for cuffless continuous BP waveform estimation using U-Net.

Continuous monitoring of blood pressure (BP) is crucial for daily healthcare. Although invasive methods provide accurate continuous BP measurements, they are not suitable for routine use. Photoplethysmography (PPG), a non-invasive technique that detects changes in blood volume within the microcirculation using light, shows promise for BP measurement. The primary goal of this study is to develop a novel cuffless method based on PPG for accurately estimating continuous BP.
Approach. We introduce BP-Diff, an end-to-end method for cuffless continuous BP waveform estimation utilizing a conditional diffusion probability model combined with a U-Net architecture. This approach takes advantage of the stochastic properties of diffusion models and the strong feature representation capabilities of U-Net. It integrates the continuous BP waveform as the initial status and uses the PPG signal and its derivatives as conditions to guide the training and sampling process.
Main results. BP-Diff was evaluated using both uncalibrated and calibrated schemes. The results indicate that, when uncalibrated, BP-Diff can accurately track BP dynamics, including peak and valley positions, as well as timing. After calibration, BP-Diff achieved highly accurate BP estimations. The mean absolute error (MAE) of the estimated BP waveforms, along with the systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) from the calibrated BP-Diff model, were 2.99 mmHg, 2.6 mmHg, 1.4 mmHg, and 1.44 mmHg, respectively. Consistency tests, including Bland-Altman analysis and Pearson correlation, confirmed its high reliability compared to reference BP. BP-Diff meets the American Association for Medical Instrumentation (AAMI) standards and has achieved a Grade A from the British Hypertension Society (BHS).
Significance. This study utilizes PPG signals to develop a novel cuffless continuous BP measurement method, demonstrating superiority over existing approaches. The method is suitable for integration into wearable devices, providing a practical solution for continuous BP monitoring in everyday healthcare.

Quantification of physiological effect of respiration on automated measurement of blood pressure among normotensive adult individuals.

Accurate blood pressure measurement necessitates meticulous methodology, as even minor variations like speaking or sitting can impact the readings. Additionally, respiration plays a role in blood pressure, exhibiting a dip during inhalation and a subsequent increase during exhalation. However, the influence of breathing patterns, duration, and rate on blood pressure remains largely unexplored. In this study, we have attempted to quantify the changes in blood pressure and heart rate (HR) of normotensive individuals while performing predefined respiratory patterns - slow, medium, and fast (respiratory rates of 5, 10, and 20/m, respectively). For each respiratory pattern, age-matched and gender-matched (18-40 years) volunteered normotensive individuals were selected as volunteers. Baseline readings were recorded and each volunteer was randomly allotted a respiratory pattern. The volunteers performed the assigned respiratory pattern while the BP and HR were recorded. A fall in both SBP and DBP was observed in all three patterns of respiration. There was no inter-pattern difference in the blood pressure change. A novel finding in our study was a trend of respiratory rate and HR - the change in HR linearly increased with a rise in respiratory rate difference. We also proposed a linear regression equation for this increase in HR with the increase in respiratory rate which was statistically significant. The findings suggest the decline in blood pressure is independent of the respiratory pattern employed. The study also demonstrates that the HR is a linear function of respiratory rate.

P066 HOW BLOOD PRESSURE DEVICES ARE OBTAINED FOR HOME BLOOD PRESSURE MEASUREMENT: A MIXED-METHODS STUDY AMONG AUSTRALIA ADULTS

Background and Objective. Only 20% of automated blood pressure (BP) devices available for purchase are validated. However, how consumers obtain devices for home BP measurement and whether their devices are validated remains unknown, which was the aim of this study. Methods. Surveys (n=225) and interviews (n=27) among adults who measure BP at home in Australia (June-December 2023). Survey questions included how the BP device was obtained, device details to determine validation status, and considerations in choosing a device. Interviews explored how and why BP devices were obtained in detail. Results. Most participants (n=216, 96%) used an upper-arm cuff device, of which 52% (n=118) were validated. Of 9 participants that used wrist cuff devices, 67% (n=6) were validated. Most participants purchased (n=176, 91%) their BP device, predominantly from pharmacy (n=126, 72%; 50% validated), followed by online (n=36, 16%; 52% validated). Validated BP devices were on average $38.53 AUD more expensive than non-validated devices (p<0.001). Although accuracy was the most important consideration when choosing a BP device (n=112, 50%), few interview participants cited device validation status as a consideration. “I just assumed that they were all accurate”. Most interview participants avoided cheaper BP devices, believing these were less accurate, and they were willing to “make an investment” in their BP device due to the importance of getting an accurate BP measurement. Interview participants rarely received recommendations from their GP about which BP device to use and reported pharmacy staff provided retail support based on in-store device availability rather than information about accuracy. Conclusion. This study found only 50% of devices used by consumers for home BP measurement have been validated. Devices that are validated are more expensive, but critically, consumers are willing to make an investment in an accurate BP device. However, little guidance is provided to support consumers when selecting a BP device. These findings demonstrate the need for credible information and resources that support consumers to obtain validated BP devices.

Abstract P315: Using Home Blood Pressure Monitors in the Office Setting as an Alternative to Automated Office Blood Pressure: A Quality Improvement Project

Background: Accurate blood pressure (BP) measurement is key to the diagnosis and effective treatment of hypertension (HTN). The U.S. HTN guideline recommends having patients rest for 5 minutes before measuring BP and obtaining at least two measurements 1-2 minutes apart. This is difficult to achieve in a busy primary care practice, and while automated office BP (AOBP) has been advanced as a solution, the required device may be cost-prohibitive. As home BP monitors are much less expensive, a protocol employing them in the office setting could prove to be an attractive alternative to AOBP. Objective: To promote the recording of multiple BP readings in primary care visits by using home BP monitors for measurement. Methods: Our primary care practice hosts 110 internal medicine residents and completes more than 35,000 patient visits annually. Prior to the intervention, medical assistants (MAs) obtained vital signs (VS) at every visit using a VS cart. In the first version of the new protocol, MAs measured all VS except BP using the VS cart, then measured BP once using an Omron 5 series BP monitor and recorded that reading in the chart. MAs left the cuff on the patient’s arm and instructed him/her to rest quietly for 5 minutes before taking a second BP reading him/herself while waiting for the provider after the MA exited the room. The patient took a third reading 1-2 minutes after the second. The provider recorded the second and third readings in the chart. Results: We implemented the new protocol in November 2023. In February 2024, we met with MAs to solicit feedback. They found the protocol easy to follow overall but had two concerns: (1) It was cumbersome to use two different devices to obtain a full set of VS; and (2) since many patients had normal BP, it did not seem worthwhile to obtain multiple BP measurements for all patients. After this meeting, we began measuring heart rate and oxygen saturation with a portable pulse oximeter instead of the VS cart, which is now only used in special circumstances. We also modified the protocol so that patients with systolic BP < 120 mm Hg and diastolic BP < 80 mm Hg are not required to obtain any repeat BP measurements. Conclusions: A new BP measurement protocol using home BP monitors to obtain multiple readings at each visit was feasible in our large academic primary care practice. We plan to investigate its effect on frequency of repeat BP measurement and likelihood of intensifying therapy for uncontrolled HTN.

O84 BLOOD PRESSURE MEASUREMENT VIA IMPEDANCE CARDIOGRAPHY: AN ARTIFICIAL INTELLIGENCE BASED PROOF-OF-CONCEPT

Objective: Accurate blood pressure (BP) measurement is crucial for the diagnosis, risk assessment, treatment decision-making, and monitoring of cardiovascular diseases. Unfortunately, the gold-standard, cuff-based BP measurement suffer from inaccuracies and discomfort. As a result, continuous, cuff-less, and non-invasive BP assessment methods are merging as promising alternatives. This study is the first to comprehensively assess impedance cardiography (ICG) for Machine Learning enabled BP measurement. Methods: We analysed ICG data from 71 young and healthy adults. Nine different Machine Learning algorithms were evaluated for their BP estimation performance. Accuracy measures comprised mean difference, standard deviation, Limits of Agreement, mean absolute error, and root mean squared error. Additionally, the B-Score was calculated to evaluate the “true”, relative performance of the best-performing model. Results: The Multi-Linear Regression model showed the highest performance (mean difference = -0.01, r = 0.82) for systolic BP. The Support Vector Regressor model achieved the best results (mean difference = 0.15, r = 0.51) for diastolic BP. Both models exhibited positive B-Scores, indicative of their predictive capability. All tested models’ estimations correlated with both systolic and diastolic reference BP (r > 0.72 / r > 0.34, p < 0.001). Conclusion: The study highlights the potential of ICG based Machine Learning algorithms for accurately estimating arterial BP. Such algorithms can provide accurate and continuous BP data. This offers the possibility of enhancing patient care, timely diagnostics, and treatment decision-making. Our approach is especially promising for post-surgical and intensive care environments.

P067 HOME BLOOD PRESSURE MEASUREMENTS ARE NOT PERFORMED ACCORDING TO GUIDELINES AND STANDARDIZED EDUCATION IS URGENTLY NEEDED: A MIXED-METHODS STUDY AMONG AUSTRALIAN ADULTS

Background and Objective. Home blood pressure (BP) measurement should be undertaken according to guideline recommendations to ensure accurate BP measurement. Patient education is required to provide knowledge and skills for home BP measurement. However, little is known about how BP is measured at home and what education is provided to patients, which was the aim of this study. Methods. A 30-item survey (n=350) and interviews (n=34) among Australian adults who measure BP at home (June–December 2023). Survey questions included steps taken and education received for home BP measurement. Interviews were conducted among a purposive sample to explore survey topics in detail. Results. No participants reported always undertaking home BP measurement according to all the guideline recommendations (Figure 1). However, most participants measured BP seated (n=316, 90%), with the cuff on a bare arm (n=269, 77%) and legs uncrossed (n=232, 66%). In addition, most participants recorded their BP measurements (n=280, 80%) and reported them to a medical professional (n=232, 79%). Interview participants reported measuring BP in an ad-hoc manner, using different steps each time they measure BP at home. “I [measure BP] at different times of the day after doing different things”. Only 37% (n=112) participants received education for home BP measurement. Interview participants who received education described healthcare practitioners giving verbal instructions for BP measurement. However, there were no differences in performing home BP measurement according to guideline recommendations between participants that received education and those that did not. In the absence of education, many interview participants described mimicking BP measurement methods of their healthcare provider. “I do it the way I’ve seen them do it”. Conclusions. This study found that home BP measurement is not performed according to guideline recommendations and standardised, high-quality education is rarely delivered on how to measure BP at home. These findings highlight an urgent need for effective education strategies to support high-quality home BP measurement to appropriately inform BP management.

O32 AVAILABILITY OF PROPERLY VALIDATED BLOOD PRESSURE MEASURING DEVICES FOR PREGNANT WOMEN: STRIDE BP SYSTEMATIC REVIEW

Background and Objective: Validated automated upper-arm cuff blood pressure (BP) measuring devices are currently recommended for BP measurement. However, a validated BP device in the general population may be inaccurate in pregnant women. Thus, separate validation studies are required in pregnant women with normal BP, hypertension, and preeclampsia. This study assessed the published evidence on BP devices in pregnancy. Methods: STRIDE BP (www.stridebp.org) performs periodic systematic PubMed searches to identify validation studies of automated cuff BP monitors. Validation studies in pregnancy conducted using an established protocol, including the AAMI/ESH/ISO Universal Standard (ISO 81060-2:2018), ANSI/AAMI/ISO 2013/2009, ESH-IP 2010/2002, AAMI 2002/1992/1987, and BHS 1993/1990, were identified. Results: Of 569 validation studies included in the STRIDE BP database, 63 (35 devices) were identified including pregnant women. Among them, STRIDE BP rejected 45 studies, of which 25 were reported as “device pass” in the published validation paper. Among the studies rejected by STRIDE BP but published as “pass”, the main reasons for rejection were violations in the BP measurement protocol (44%), inadequate reference device or cuffs for reference and test device (36%), no data in women with hypertension and/or preeclampsia (36%), single observer for reference BP measurement (28%), and inappropriate data analysis (20%). Eventually 18 studies in pregnant women (28.6%) fulfilled the protocol requirements, and 16 devices (8 of them available on the market) can be recommended for clinical use in pregnancy. When additional ‘equivalent’ devices were considered (devices lacking validation studies but with differences from validated devices not affecting the BP measurement accuracy), 37 devices were found to be accurate in pregnancy, with 27 of them available on the market (Table). Conclusions: This analysis showed a shortage of properly validated BP devices for pregnant women available in the market, with published validation often having major methodological issues. There is an urgent need to develop and properly validate more BP devices in pregnancy. TABLE. Validated devices for office, home, and ambulatory BP measurement in pregnant women.

Investigating the Sources of Variability in Blood Pressure Monitoring Systems

Accurate and reliable blood pressure measurement is critical for diagnosing and managing hypertension properly. Based on a consensus document announced in the Journal of Hypertension, this is so much so that a 5.0 mm Hg BP measurement error can result in incorrect hypertension classification in 84 million individuals worldwide. Understanding how BP measurement goes wrong and how to tackle them can improve the diagnosis and management of hypertension. Unfortunately, BP measurement is problematically performed in clinical practice, accumulating errors that inappropriately alter management decisions in 20% to 45% of cases. In this study, the sources of variability from the aspects of the blood pressure monitoring system were attempted to be scrutinized. The variability increases with additive properties such as pressure gauge inaccuracy, cuff tightness, and cloth over-measurement. An artificial plastic arm was created to measure the pressure with multiple monitors. The study concluded that each monitor had its inherent characteristics in increasing monitor pressures concerning the actual pressure, and further, the increases in cuff loosening distance and the cloth-over layers might cause more significant variability, as hypothesized in this study. The study could more clearly verify the reason for blood pressure measurement variability.

A Wireless Noninvasive Blood Pressure Measurement System Using MAX30102 and Random Forest Regressor for Photoplethysmography Signals

Hypertension, often termed “the silent killer”, is associated with cardiovascular risk and requires regular blood pressure (BP) monitoring. However, existing methods are cumbersome and require medical expertise, which is worsened by the need for physical contact, particularly during situations such as the coronavirus pandemic that started in 2019 (COVID-19). This study aimed to develop a cuffless, continuous, and accurate BP measurement system using a photoplethysmography (PPG) sensor and a microcontroller via PPG signals. The system utilizes a MAX30102 sensor and ESP-WROOM-32 microcontroller to capture PPG signals that undergo noise reduction during preprocessing. Peak detection and feature extraction algorithms were introduced, and their output data were used to train a machine learning model for BP prediction. Tuning the model resulted in identifying the best-performing model when using a dataset from six subjects with a total of 114 records, thereby achieving a coefficient of determination of 0.37/0.46 and a mean absolute error value of 4.38/4.49 using the random forest algorithm. Integrating this model into a web-based graphical user interface enables its implementation. One probable limitation arises from the small sample size (six participants) of healthy young individuals under seated conditions, thereby potentially hindering the proposed model’s ability to learn and generalize patterns effectively. Increasing the number of participants with diverse ages and medical histories can enhance the accuracy of the proposed model. Nevertheless, this innovative device successfully addresses the need for convenient, remote BP monitoring, particularly during situations like the COVID-19 pandemic, thus making it a promising tool for cardiovascular health management.

Accurate Blood Pressure Measurement Using Smartphone's Built-in Accelerometer

Efficient blood pressure (BP) monitoring in everyday contexts stands as a substantial public health challenge that has garnered considerable attention from both industry and academia. Commercial mobile phones have emerged as a promising tool for BP measurement, benefitting from their widespread popularity, portability, and ease of use. Most mobile phone-based systems leverage a combination of the built-in camera and LED to capture photoplethysmography (PPG) signals, which can be used to infer BP by analyzing the blood flow characteristics. However, due to low Signal-to-Noise (SNR), various factors such as finger motion, improper finger placement, skin tattoos, or fluctuations in environmental lighting can distort the PPG signal. These distortions consequentially affect the performance of BP estimation. In this paper, we introduce a novel sensing system that utilizes the built-in accelerometer of a mobile phone to capture seismocardiography (SCG) signals, enabling accurate BP measurement. Our system surpasses previous mobile phone-based BP measurement systems, offering advantages such as high SNR, ease of use, and power efficiency. We propose a triple-stage noise reduction scheme, integrating improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), recursive least squares (RLS) adaptive filter, and soft-thresholding, to effectively reconstruct high-quality heartbeat waveforms from initially contaminated raw SCG signals. Moreover, we introduce a data augmentation technique encompassing normalization coupled with temporal-sliding, effectively augmenting the diversity of the training sample set. To enable battery efficiency on smartphone, we propose a resource-efficient deep learning model that incorporates resource-efficient convolution, shortcut connections, and Huber loss. We conduct extensive experiments with 70 volunteers, comprising 35 healthy individuals and 35 individuals diagnosed with hypertension, under a user-independent setting. The excellent performance of our system demonstrates its capacity for robust and accurate daily BP measurement.

Possibilities to increase reliability and accuracy of blood pressure measurement taking into account blood hydrodynamics and biomechanics of processes during compression of shoulder tissues with a pneumatic cuff

Systolic and diastolic BP values are determined guided by measurement signals (Korotkoff tones, oscillations). The source of these signals are hydrodynamic processes occurring in the artery under the influence of cuff pressure on the upper arm. The article is devoted to the study of these processes. The value of body tissues pressure on the artery walls is equal to the value of air pressure in the cuff only at the middle of the cuff and smoothly decreases to zero to its edges. Such non-uniformity of distribution of body tissues pressure on the artery walls is caused by the physical property of elasticity of their shape, which was not taken into account earlier. Therefore, the equality of the value of blood pressure on the artery walls from its inner side and the value of body tissues pressure on the artery walls from its outer side is possible only at one point. At this point, the open part of the artery passes into its constricted part, and the point itself is called the boundary of arterial constriction. The pulsations of blood pressure in the artery caused by the heart cause rhythmic movements of this boundary along the artery. Therefore, the arterial walls open up when the constriction boundary is moved in the distal direction. When the convergence boundary is moved in the proximal direction, the walls of the artery connect. During systole, when the blood pressure exceeds the air pressure in the cuff, the boundary of compression moves distally across the middle of the cuff. At the same time, a blood flow front is formed beyond the middle of the cuff, moving towards the distal edge of the cuff. When this edge is reached, the artery opens across the entire width of the cuff. In the diastole periods following systole, the blood pressure decreases. As a result, the blood pressure drops below the air pressure in the cuff, and the arterial wall at the midpoint of the cuff interconnect again. In this case, there is a re-boundary of constriction moving in the proximal direction. Thus, the hydrodynamics of blood in the artery is completely determined by the movements of the boundary of its compression. This hydrodynamics is substantiated theoretically and confirmed experimentally. It is shown that oscillations of air pressure in the cuff, Korotkoff tones and surface pulse waves are different consequences of a single biomechanical process, which allows us to consider in detail the formation of oscillations, surface pulse waves, as well as to put forward a physically justified version of the Korotkoff tones.

OFFICE BP MEASUREMENT USING CONICAL CUFFS IN OBESE CHILDREN AND ADOLESCENTS

Objective: Findings from adult studies suggest that tronco-conical cuffs should be used for accurate blood pressure (BP) measurement in obese individuals with large arm circumference (AC). The aim of the present study was to examine differences in office blood pressure (BP) levels using conical cuffs compared to standard-shaped cylindrical cuffs in obese children and adolescents. Design and method: We performed an observational study enrolling 37 obese children and adolescents consequently recruited from the outpatient clinics of the Obesity Unit at General University Hospital Consortium of Valencia. The device used for the office BP measurements was OMRON HBP-1320 (HBP-1320-E). Middle AC was measured in all participants and the appropriate cuff size was selected among five sizes of conical and three sizes of regular cylindrical cuffs. Results: Mean participants’ age was 11.8±2.5 years, mean BMI was 28.8±3.4 kg/m2, BMI z-score was 2.1 ± 0.3, and mean AC was 30.0±3.6 cm. There was no statistical significance in BP levels measured by cylindrical compared to conical cuffs (mean difference cylindrical-conical cuff was -0.22±6.55 mmHg for SBP, -0.02±0.81 for SBP z-score, -0.70±4.95 mmHg for DBP, and -0.06±0.44 for DBP z-score). The analysis was repeated after excluding participants aged <9 years old, retrieving similar results. A significant positive association was found between the measurements obtained by cylindrical and conical cuffs in both mean and z-score SBP and DBP values (p <0.001). Bland-Altman analysis showed good agreement, with 94.6% of the values for all BP parameters, lying between the limits of agreement. No proportional bias was detected (p >0.05). Conclusions: The use of conical cuffs resulted in similar office BP levels in obese children and adolescents suggesting no advantage in enhancing tolerability and accuracy of office BP measurement in these patients. Although conical cuffs may be considered an alternative for office BP measurements in obese children, their reliability should be confirmed in larger populations and different settings. Acknowledgments: This abstract is based on the work of the COST Action HyperChildNET (CA19115), with the support of COST (European Cooperation in Science and Technology) and the Horizon 2020 Framework Program of the European Union.

UNATTENDED AUTOMATIC BLOOD PRESSURE MEASUREMENTS VS. CONVENTIONAL OFFICE READINGS IN PREDICTING HYPERTENSION-MEDIATED ORGAN DAMAGE

Objective: Hypertension, a major cardiovascular risk, requires accurate blood pressure measurement. Conventional office measurements (OBPM) are error-prone and systematically biased by the white coat effect. Unattended office blood pressure measurement (UOBPM) is emerging as an alternative to mitigate this bias. However, its ability to predict hypertension-mediated organ damage (HMOD), indicating disease progression, remains debated. This study compares UOBPM with OBPM in terms of their association with various HMODs, including left ventricular hypertrophy (LVH), left atrial enlargement (LAE), left ventricular systolic and diastolic dysfunction, intima-media complex (IMT) thickening, microalbuminuria and abnormal pulse wave velocity (PWV). Design and method: Hypertensive patients without overt cardiovascular disease were recruited, interviewed, and examined. Subsequently, blood pressure measurements were conducted in standard conditions in a randomized sequence in each patient: 1) UOBPM: After 5 minutes of solitary rest in the examination room, blood pressure was automatically measured three times at 1-minute intervals with OMRON HEM 907 device. 2) OBPM: After 5 minutes of rest, a physician performed three automated measurements at 1-minute intervals with the same device. Subsequent evaluations aimed to detect HMODs, including echocardiography, carotid artery ultrasound, PWV assessment, and laboratory tests. Receiver operating characteristic (ROC) analysis was performed for each HMOD in both measurement groups, and the areas under the ROC curves were compared. Results: The study enrolled 219 patients(55% females, mean age 55 ±14 years). The average systolic blood pressure in UOBPM was lower by 4,2 mmHg (p<0,001) compared to OBP while the difference in diastolic pressure was 1,9 mmHg (p<0,001). Both measurement methods were associated with the presence of the following HMODs: LAE, IMT thickening, and abnormal PWV. Neither method allowed for the prediction of LVH, systolic and diastolic dysfunction of the left ventricle, elevated ACR, or the presence of atherosclerotic plaques in the carotid arteries. Furthermore, ROC curve analyses revealed no difference between the two methods in predicting HMOD (Table 1). Conclusions: Both measurement techniques exhibited satisfactory predictive ability for the presence of certain HMOD. However, based on the study results, no significant differences could be inferred between the two methods with respect to their predictive performance.

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

Convenient and accurate blood pressure (BP) measurement is of great importance in both clinical and daily life. Although deep learning (DL) can achieve cuff-less BP measurement based on Photoplethysmography (PPG), the performance of DL is affected by few-shot data. Data augmentation becomes an effective way to enhance the size of the training data. In this paper, we use cropping, flipping, DTW barycentric averaging (DBA), generative adversarial network (GAN) and variational auto-encoder (VAE) for the data augmentation of PPG. Furthermore, a PE–CNN–GRU model is designed for cuff-less BP measurement applying position encoding (PE), convolutional neural networks (CNNs) and gated recurrent unit (GRU) networks. Experiment results based on real-life datasets show that VAE is the most suitable method for PPG data augmentation, which can reduce the mean absolute error (MAE) of PE–CNN–GRU when measuring systolic blood pressure (SBP) and diastolic blood pressure (DBP) by 18.80% and 19.84%. After the data augmentation of PPG, PE–CNN–GRU achieves accurate and cuff-less BP measurement, thus providing convenient support for preventing cardiovascular diseases.

Unattended automatic blood pressure measurements vs conventional office readings in predicting hypertension-mediated organ damage.

Hypertension is a leading cardiovascular risk factor. Accurate blood pressure (BP) measurement is pivotal in hypertension diagnosis and management. Conventional office blood pressure measurements (OBPMs) are error‑prone, exacerbated by the white‑coat effect. Unattended automated office blood pressure measurement (UAOBPM) is emerging as an alternative, mitigating the white‑coat effect. However, its ability to predict hypertension‑mediated organ damage (HMOD) remains disputable. This study compares UAOBPM with OBPM in terms of their association with various types of HMOD, including left ventricular hypertrophy, left atrial enlargement, left ventricular systolic and diastolic dysfunction, intima‑media complex thickening, microalbuminuria, and abnormal pulse wave velocity. A total of 219 hypertensive patients were recruited, interviewed, and examined. Subsequently, BP measurements were conducted in a randomized manner: 1) UAOBPM, after 5 minutes of solitary rest in an examination room, BP was automatically measured 3 times at 1‑minute intervals; 2) OBPM, after 5 minutes of rest, a physician performed 3 consecutive BP measurements at 1‑minute intervals. Subsequent evaluations aimed to detect HMOD and included echocardiography, carotid artery ultrasound, pulse wave velocity assessment, and laboratory tests. UAOBP values were lower than the OBP ones (mean [SD], 124.7 [14.4] vs 128.2 [14.2] mm Hg; P <0.001 for systolic BP, and 73.3 [10.2] vs 75.2 [10.6] mm Hg; P <0.001 for diastolic BP). Correlation and receiver operating characteristic curve analyses revealed no superiority of either method in predicting HMOD. The UAOBPM did not prove superior to OBPM in predicting HMOD. Further research is warranted to determine the role of UAOBPM in clinical practice.

Evaluation of the oscillometric method for noninvasive blood pressure measurement during cuff deflation and cuff inflation with reference to intra-arterial blood pressure.

There is little quantitative clinical data available to support blood pressure measurement accuracy during cuff inflation. In this study of 35 male and 5 female lightly anaesthetized subjects aged 64.1 ± 9.6 years, we evaluate and compare the performance of both the oscillometric ratio and gradient methods during cuff deflation and cuff inflation with reference to intra-arterial measurements. We show that the oscillometric waveform envelopes (OWE), which are key to both methods, exhibit significant variability in both shape and smoothness leading to at least 15% error in the determination of mean pressure (MP). We confirm the observation from our previous studies that K1 Korotkoff sounds underestimate systolic blood pressure (SBP) and note that this underestimation is increased during cuff inflation. The estimation of diastolic blood pressure (DBP) is generally accurate for both the ratio and the gradient method, with the latter showing a significant increase during inflation. Since the gradient method estimates SBP and DBP from points of maximum gradient on each OWE recorded, it may offer significant benefits over the ratio method. However, we have shown that the ratio method can be optimized for any data set to achieve either a minimum mean error (ME) of close to 0 mmHg or minimum root mean square error (RMSE) with standard deviation (SD) of <5.0 mmHg. We conclude that whilst cuff inflation may offer some advantages, these are neither significant nor substantial, leaving as the only benefit, the potential for more rapid measurement and less patient discomfort.

Noninvasive Blood Pressure Monitoring via a Flexible and Wearable Piezoresistive Sensor.

In the present global context, continuous blood pressure (BP) monitoring is paramount in addressing the global mortality rates attributed to hypertension. Achieving precise insights into the human cardiovascular system necessitates accurate measurement of BP, and the accuracy depends on the faithful recording of oscillations or pulsations. This task ultimately depends on the caliber of the pressure sensor embedded in the BP device. In this context, we have fabricated a flexible resistive pressure sensor based on reduced graphene oxide (rGO) and a polydimethylsiloxane (PDMS) sponge that is highly flexible and sensitive. The designed device operates effectively with a minimal bias voltage of 500 mV, at which point it showed its maximum relative change in current, reaching approximately 25%. Additionally, the sensing device showed a notable change in resistance values, exhibiting almost 100% change in resistance when subjected to a pressure of 400 mmHg and high sensitivity of 0.27 mmHg-1. After promising outcomes were obtained during static pressure measurement, the sensor was used for BP monitoring in humans. The sensor accurately traced the oscillometric waveform (OMW) for distinct systolic blood pressure (SBP) and diastolic blood pressure (DBP) combinations to cover a range of medical situations, including hypotension, standard or normal, and hypertension. The values of SBP, DBP, and MAP were derived from the sensor's output using the MAA technique, and the errors in these values concerning the simulator and the traditional BP monitor follow the universal AAMI/ESH/ISO protocols. Bland-Altman (B&A) correlation and scatter plots were used to compare the sensor's results and further validate the proposed sensor. The sensor showed the mean and standard deviation error in the SBP, DBP, and MBP of -0.2 ± 5.9, -0.5 ± 7, and -0.9 ± 4.7 mmHg when compared with the noninvasive blood pressure (NIBP) simulator. The pulse rate (PR) was also calculated from the same OMW for the specified value of 80 beats per minute (bpm) given by the simulator and reported a mean PR value of ∼81 bpm, close to the reference value. The findings show that the flexible resistive sensing device can accurately measure BP and replace the existing sensors of BP devices.