Continuous Blood Pressure Monitoring Research Articles

New approaches for rapid setpoint determination and uninterrupted tracking in non-invasive continuous blood pressure monitoring based on volume-clamp method

The volume-clamp method (VCM) is a widely used non-invasive continuous blood pressure (BP) monitoring technique, but determining the volume setpoint (V0) in the open-loop phase can be time-consuming and may cause finger tissue displacement. Additionally, frequent interruptions in BP measurement are required during the closed-loop phase to reset V0. We proposed two new approaches: the proportional value method (PVM) for rapid V0 determination in the open-loop phase and the uninterrupted V0 tracking method (UVTM) in the closed-loop phase. PVM adaptively searches for V0 by analyzing the shape index (Prop) of the plethysmographic (PG) signal under constant cuff pressure, while UVTM introduces a new vascular compliance calculation method in closed-loop phase to track changes in V0 without interrupting BP measurement. We describe the non-invasive continuous BP monitor (NC-BPM) based on these methods. Experimental results show that PVM can accurately determine V0, with a mean arterial pressure error of −1.72 ± 2.80 mmHg when compared to oscillometric method (OSCM). UVTM in NC-BPM produced a mean absolute error (MAE) of 2.44 ± 2.91 mmHg for mean arterial pressure (MAP) in induced BP fluctuation test compared to the Nexfin monitor. In the clinical study with invasive reference, the MAE in measuring MAP by NC-BPM was 4.69 ± 5.39 mmHg. Our results show that PVM and UVTM are highly accurate and reliable, with the potential to integrate effectively into VCM-based BP monitoring devices that could benefit patients, healthcare providers, and researchers.

The identification of blood pressure variation with hypovolemia based on the volume compensation method.

Objective: The purpose of this study is to identify the blood pressure variation, which is important in continuous blood pressure monitoring, especially in the case of low blood volume, which is critical for survival. Methods: A pilot study was conducted to identify blood pressure variation with hypovolemia using five Landrace pigs. New multi-dimensional morphological features of Photoplethysmography (PPG) were proposed based on experimental study of hemorrhagic shock in pigs, which were strongly correlated with blood pressure changes. Five machine learning methods were compared to develop the blood pressure variation identification model. Results: Compared with the traditional blood pressure variation identification model with single characteristic based on single period area of PPG, the identification accuracy of mean blood pressure variation based on the proposed multi-feature random forest model in this paper was up to 90%, which was 17% higher than that of the traditional blood pressure variation identification model. Conclusion: By the proposed multi-dimensional features and the identification method, it is more accurate to detect the rapid variation in blood pressure and to adopt corresponding measures. Significance: Rapid and accurate identification of blood pressure variation under low blood volume ultimately has the potential to effectively avoid complications caused by abnormal blood pressure in patients with clinical bleeding trauma.

Transforming blood pressure control in primary care through a novel remote decision support strategy based on wearable blood pressure monitoring: The NEXTGEN-BP randomized trial protocol

Despite high blood pressure being the leading preventable risk factor for death, only 1 in 3 patients achieve target blood pressure control. Key contributors to this problem are clinical inertia and uncertainties in relying on clinic blood pressure measurements to make treatment decisions. The NEXTGEN-BP open-label, multicenter, randomized controlled trial will investigate the efficacy, safety, acceptability and cost-effectiveness of a wearable blood pressure monitor-based care strategy for the treatment of hypertension, compared to usual care, in lowering clinic blood pressure over 12 months. NEXTGEN-BP will enroll 600 adults with high blood pressure, treated with 0 to 2 antihypertensive medications. Participants attending primary care practices in Australia will be randomized 1:1 to the intervention of a wearable-based remote care strategy or to usual care. Participants in the intervention arm will undergo continuous blood pressure monitoring using a wrist-wearable cuffless device (Aktiia, Switzerland) and participate in 2 telehealth consultations with their primary care practitioner (general practitioner [GP]) at months 1 and 2. Antihypertensive medication will be up-titrated by the primary care practitioner at the time of telehealth consults should the percentage of daytime blood pressure at target over the past week be <90%, if clinically tolerated. Participants in the usual care arm will have primary care consultations according to usual practice. The primary outcome is the difference between intervention and control in change in clinic systolic blood pressure from baseline to 12 months. Secondary outcomes will be assessed at month 3 and month 12, and include acceptability to patients and practitioners, cost-effectiveness, safety, medication adherence and patient engagement. NEXTGEN-BP will provide evidence for the effectiveness and safety of a new paradigm of wearable cuffless monitoring in the management of high blood pressure in primary care. ACTRN12622001583730.

Remote Estimation of Blood Pressure Using Millimeter-Wave Frequency-Modulated Continuous-Wave Radar.

This paper proposes to remotely estimate a human subject's blood pressure using a millimeter-wave radar system. High blood pressure is a critical health threat that can lead to diseases including heart attacks, strokes, kidney disease, and vision loss. The commonest method of measuring blood pressure is based on a cuff that is contact-based, non-continuous, and cumbersome to wear. Continuous remote monitoring of blood pressure can facilitate early detection and treatment of heart disease. This paper investigates the possibility of using millimeter-wave frequency-modulated continuous-wave radar to measure the heart blood pressure by means of pulse wave velocity (PWV). PWV is known to be highly correlated with blood pressure, which can be measured by pulse transit time. We measured PWV using a two-millimeter wave radar focused on the subject's chest and wrist. The measured time delay provided the PWV given the length from the chest to the wrist. In addition, we analyzed the measured radar signal from the wrist because the shape of the pulse wave purveyed information on blood pressure. We investigated the area under the curve (AUC) as a feature and found that AUC is strongly correlated with blood pressure. In the experiment, five human subjects were measured 50 times each after performing different activities intended to influence blood pressure. We used artificial neural networks to estimate systolic blood pressure (SBP) and diastolic blood pressure (SBP) with both PWV and AUC as inputs. The resulting root mean square errors of estimated blood pressure were 3.33 mmHg for SBP and 3.14 mmHg for DBP.

Continuous Blood Pressure Monitoring in Patients Having Surgery: A Narrative Review.

Hypotension can occur before, during, and after surgery and is associated with postoperative complications. Anesthesiologists should thus avoid profound and prolonged hypotension. A crucial part of avoiding hypotension is accurate and tight blood pressure monitoring. In this narrative review, we briefly describe methods for continuous blood pressure monitoring, discuss current evidence for continuous blood pressure monitoring in patients having surgery to reduce perioperative hypotension, and expand on future directions and innovations in this field. In summary, continuous blood pressure monitoring with arterial catheters or noninvasive sensors enables clinicians to detect and treat hypotension immediately. Furthermore, advanced hemodynamic monitoring technologies and artificial intelligence-in combination with continuous blood pressure monitoring-may help clinicians identify underlying causes of hypotension or even predict hypotension before it occurs.

Assessment of daily blood pressure parameters in patients after injury

ABSTRACT. Many studies have highlighted the impact of various significant risk factors on the occurrence of arterial hypertension. However, few papers have examined the effect of psychoemotional factors as important contributors to the risk of arterial hypertension for such a specific population group as contracted servicemen performing military service under conditions of performing special tasks. Furthermore, there is a lack of data on the daily profile of blood pressure in this particular group of individuals. This thesis aims to substantiate the claim that injury, as a risk factor, greatly influences changes in the daily profile of blood pressure. The study examined 118 patients, divided into an experimental group (65 people) and a control group (53 people). The daily profile of blood pressure was assessed using continuous ambulatory blood pressure monitoring. Questionnaires were used to evaluate the quality of sleep, anxiety, and depression. The findings indicated that the patients of the experimental group, following trauma, exhibited a higher index of systolic and diastolic blood pressure duration, while the mean values remained within the normal range. Additionally, these patients more frequently exhibited a blood pressure profile characterized by an insufficient nocturnal decrease in blood pressure, known as non-dipping. This could be attributed to impaired sleep quality, as well as subclinically significant manifestations of anxiety and depression caused by stress. The early detection of changes in the index of systolic and diastolic blood pressure duration, along with deviations in the daily blood pressure profile observed through continuous ambulatory blood pressure monitoring, would enable specialists to promptly address alterations in the hemodynamics of these patients and prescribe appropriate therapy. Therefore, psychoemotional stress in people who have experienced trauma is one of the trigger mechanisms for increased blood pressure. If left unaddressed, this can progress to persistent arterial hypertension.

Noninvasive Cuffless Blood Pressure Monitoring. How Mechanism-Driven and Data-Driven Models Can Help in Clinical Practice

Continuous noninvasive cuffless blood pressure (BP) monitoring is essential for early detection and treatment of hypertension. In this paper, we provide an overview of the recent advancements in cuffless BP sensors. These include contact wearable sensors such as electrocardiography (ECG), photoplethysmography (PPG), contact non-wearable sensors such as ballistocardiography (BCG), and contactless sensors such as video plethysmography (VPG). These sensors employ different measuring mechanisms such as pulse arrival time (PAT), pulse transit time (PTT), and pulse wave analysis (PWA) to estimate BP. However, challenges exist in the effective use and interpretation of signal features to obtain clinically reliable BP measurements. The correlations between signal features and BP are obtained by mechanism-driven models which use physiological principles to identify mathematical correlations, and data-driven models which use machine learning algorithms to analyze observational data to identify multidimensional correlations. On the one hand, applying mechanism-driven models to non-linear scenarios and incomplete or noisy data is challenging On the other hand, data-driven models require a large amount of data in order to prevent physically inconsistent predictions, resulting in poor generalization. From this perspective, this paper proposes to combine the strengths of mechanism-driven and data-driven approaches to obtain a more comprehensive approach, the physiology-informed machine-learning approach, with the goal of enhancing the accuracy, interpretability, and scalability of continuous cuffless BP monitoring. This holds promise for personalized clinical applications and the advancement of hypertension management.

Patent landscape review of non-invasive medical sensors for continuous monitoring of blood pressure and their validation in critical care practice.

Continuous non-invasive monitoring of blood pressure is one of the main factors in ensuring the safety of the patient's condition in anesthesiology, intensive care, surgery, and other areas of medicine. The purpose of this work was to analyze the current patent situation and identify directions and trends in the application of non-invasive medical sensors for continuous blood pressure monitoring, with a focus on clinical experience in critical care and validation thereof. The research results reflect data collected up to September 30, 2022. Patent databases, Google Scholar, the Lens database, Pubmed, Scopus databases were used to search for patent and clinical information. An analysis of the patent landscape indicates a significant increase in interest in the development of non-invasive devices for continuous blood pressure monitoring and their implementation in medical practice, especially in the last 10 years. The key players in the intellectual property market are the following companies: Cnsystems Medizintechnik; Sotera Wireless INC; Tensys Medical INC; Healthstats Int Pte LTD; Edwards Lifesciences Corp, among others. Systematization of data from validation and clinical studies in critical care practice on patients with various pathological conditions and ages, including children and newborns, revealed that a number of non-invasive medical sensor technologies are quite accurate and comparable to the "gold standard" continuous invasive blood pressure monitoring. They are approved by the FDA for medical applications and certified according to ISO 81060-2, ISO 81060-3, and ISO/TS 81060-5. Unregistered and uncertified medical sensors require further clinical trials. Non-invasive medical sensors for continuous blood pressure monitoring do not replace, but complement, existing methods of regular blood pressure measurement, and it is expected to see more of these technologies broadly implemented in the practice in the near future.

Automatic and continuous blood pressure monitoring via an optical-fiber-sensor-assisted smartwatch

Automatic and continuous blood pressure monitoring is important for preventing cardiovascular diseases such as hypertension. The evaluation of medication effects and the diagnosis of clinical hypertension can both benefit from continuous monitoring. The current generation of wearable blood pressure monitors frequently encounters limitations with inadequate portability, electrical safety, limited accuracy, and precise position alignment. Here, we present an optical fiber sensor-assisted smartwatch for precise continuous blood pressure monitoring. A fiber adapter and a liquid capsule were used in the building of the blood pressure smartwatch based on an optical fiber sensor. The fiber adapter was used to detect the pulse wave signals, and the liquid capsule was used to expand the sensing area as well as the conformability to the body. The sensor holds a sensitivity of -213µw/kPa, a response time of 5 ms, and high reproducibility with 70,000 cycles. With the assistance of pulse wave signal feature extraction and a machine learning algorithm, the smartwatch can continuously and precisely monitor blood pressure. A wearable smartwatch featuring a signal processing chip, a Bluetooth transmission module, and a specially designed cellphone APP was also created for active health management. The performance in comparison with commercial sphygmomanometer reference measurements shows that the systolic pressure and diastolic pressure errors are -0.35 ± 4.68 mmHg and -2.54 ± 4.07 mmHg, respectively. These values are within the acceptable ranges for Grade A according to the British Hypertension Society (BHS) and the Association for the Advancement of Medical Instrumentation (AAMI). The smartwatch assisted with an optical fiber is expected to offer a practical paradigm in digital health.

A Baseline-Tracking Single-Channel I/Q Impedance Plethysmogram IC for Neckband-Based Blood Pressure and Cardiovascular Monitoring

An impedance plethysmogram (IPG) IC with wide-range fine baseline tracking capability is proposed to provide continuous blood pressure (BP) and cardiovascular monitoring just by wearing a neckband wearable device. For the baseline tracking, a mixed-mode baseline cancellation (MM-BC) scheme is proposed to achieve wide dynamic range (DR) and high SNR performance, where an artifact-detecting continuous-time (CT)- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Delta \Sigma $</tex-math> </inline-formula> ADC is included together for high-resolution conversion. For cost-effective IPG design, a phase synchronizer concept is introduced to provide I/Q detection capability with single readout channel, supporting both configurations of two-electrode and four-electrode. A proposed readout integrated circuit (ROIC) prototype for the proposed IPG was fabricated, where an electrocardiogram (ECG) readout path is integrated together. The proposed IPG schemes were experimentally verified to achieve good performances of 145.2-dB DR and 103.5-dB SNR. For system-level feasibility, a neckband device prototype was also manufactured, and its cardiovascular monitoring functionality was functionally verified. Based on its IPG and ECG measurements, continuous BP measurement based on the pulse arrival time (PAT) was experimentally verified with a reference BP device.

Noninvasive Cuffless Blood Pressure Estimation With Dendritic Neural Regression.

Blood pressure (BP) is one of the most important indicators of health. BP that is too high or too low causes varying degrees of diseases, such as renal impairment, cerebrovascular incidents, and cardiovascular diseases. Since traditional cuff-based BP measurement techniques have the drawbacks of patient discomfort and the impossibility of continuous BP monitoring, noninvasive cuffless continuous BP measurement has become a popular topic. The common noninvasive approach uses machine-learning (ML) algorithms to estimate BP by using the features extracted from simultaneous photoplethysmogram (PPG) and electrocardiogram (ECG) signals, such as the pulse transit time and pulse wave velocity. This study investigates the BP estimation performance of the novel dendritic neural regression (DNR) method proposed by us. Unlike conventional neural networks, DNR utilizes the multiplication operator as the excitation function in each dendritic branch, inspired by biological neuron phenomena, and can effectively capture nonlinear relationships between distinct input features. In addition, AMSGrad is used as the optimization algorithm to further enhance the dendritic neural model's performance. The experimental results show that by being fed a combination of the raw features extracted from the ECG and PPG signals and the components of the BP mathematical models, DNR can increase the accuracy of systolic BP, diastolic BP, and mean arterial pressure estimation significantly, which are superior to the state-of-the-art ML techniques. According to the British Hypertension Society protocol, DNR achieves a grade of A for the long-term BP estimation. Considering its architectural simplicity and powerful performance, the proposed method can be regarded as a reliable tool for estimating long-term continuous BP in a noninvasive cuffless way.

A Hemodynamic Pulse Wave Simulator Designed for Calibration of Local Pulse Wave Velocities Measurement for Cuffless Techniques.

Devices for cuffless blood pressure (BP) measurement have become increasingly widespread in recent years. Non-invasive continuous BP monitor (BPM) devices can diagnose potential hypertensive patients at an early stage; however, these cuffless BPMs require more reliable pulse wave simulation equipment and verification methods. Therefore, we propose a device to simulate human pulse wave signals that can test the accuracy of cuffless BPM devices using pulse wave velocity (PWV). We design and develop a simulator capable of simulating human pulse waves comprising an electromechanical system to simulate the circulatory system and an arm model-embedded arterial phantom. These parts form a pulse wave simulator with hemodynamic characteristics. We use a cuffless device for measuring local PWV as the device under test to measure the PWV of the pulse wave simulator. We then use a hemodynamic model to fit the cuffless BPM and pulse wave simulator results; this model can rapidly calibrate the cuffless BPM's hemodynamic measurement performance. We first used multiple linear regression (MLR) to generate a cuffless BPM calibration model and then investigated differences between the measured PWV with and without MLR model calibration. The mean absolute error of the studied cuffless BPM without the MLR model is 0.77 m/s, which improves to 0.06 m/s when using the model for calibration. The measurement error of the cuffless BPM at BPs of 100-180 mmHg is 1.7-5.99 mmHg before calibration, which decreases to 0.14-0.48 mmHg after calibration. This study proposes a design of a pulse wave simulator based on hemodynamic characteristics and provides a standard performance verification method for cuffless BPMs that requires only MLR modeling on the cuffless BPM and pulse wave simulator. The pulse wave simulator proposed in this study can be used to quantitively assess the performance of cuffless BPMs. The proposed pulse wave simulator is suitable for mass production for the verification of cuffless BPMs. As cuffless BPMs become increasingly widespread, this study can provide performance testing standards for cuffless devices.

Barriers to Technology Adoption by Patients and Providers in Diabetes and Hypertension Care Management

Remote monitoring has been demonstrated to be an effective tool for decreasing costs and improving outcomes, however, both patients and providers have shown a reluctance to embrace technology. This survey-based, cross-sectional designed study assessed the barriers faced by patients and providers in the District of Columbia for technology adoption in remote monitoring. The patients had a diagnosis of either diabetes, hypertension, or both conditions, and utilized the technology of a home blood glucose monitor, continuous glucose monitor or ambulatory blood pressure monitor. The surveyed providers included staff engaged in chronic disease management of patients with diabetes and hypertension. An adapted version of the Barriers to Health Promoting Activities for Disabled Persons Scale (BHADP)was administered to study participants and statistically analyzed. Data analysis compared and contrasted demographics and survey responses and revealed that there is a discordance in the ways that patients perceive the barriers to technology as compared to the ways that providers perceive them. Data analysis also revealed significant system barriers that limited providers use of remote monitoring technologies. A model is proposed that identifies inputs and barriers experienced by the patient in their journey to initiate or continue a technology (adapted from Moore et al.’s 2021 Conceptual Model).

Fabric‐Based Ultrasonic Sensor with Integrated Piezoelectric Composite for Blood Pressure Monitoring

AbstractBlood pressure is an important indicator that reflects human health status. Since long‐term monitoring of blood pressure waveforms can provide important information for the diagnosis and prevention of cardiovascular disease. Wearable, non‐invasive, and continuous monitoring of blood pressure waveforms have become a current research hotspot. In this paper, a fabric‐based ultrasound sensors are produced for continuous non‐invasive monitoring of blood pressure waveforms by combining an “S”‐shaped stretchable island bridge electrode with a fabric substrate utilizing hot press transfer. The results show that the 4 × 5 array ultrasound sensors can locate arterial vessels deep in the tissue, allowing accurate, and continuous monitoring of blood pressure. Its axial resolution can reach 330 µm, and the elongation at the break of the “S”‐shaped electrode can reach 35.6%. The prepared sensor has good air permeability and stability, and does not cause skin irritation during long‐term wear.

Effect of Sleep Duration on Blood Pressure in Patients with SARS-CoV-2 Infection and Hypertensive Urgencies in Shanghai Fangcang Shelter Hospital.

To evaluate the effect of sleep duration on blood pressure in patients with hypertension urgencies combined with SARS-CoV-2 infection in a Fangcang shelter hospital. From April 10, 2020 to May 20, 2022, we statistically analyzed the blood pressure and sleep conditions of 52 patients with combined hypertension urgencies and SARS-CoV-2 infection admitted in Shanghai National Convention and Exhibition Center Fangcang shelter hospital. They were divided into the short-term (daily sleep duration: <7 h) and normal sleep group (7-9 h). We performed a comparison of the control effects of basic antihypertensive drugs. Additionally, patients in the short-term sleep group underwent drug therapy for sleep regulation and continuous monitoring of blood pressure. Among these patients, the blood pressure was higher in the short-term sleep group than that of the normal sleep group, and also more difficult to control (p <0.05). Furthermore, the blood pressure of the patients in the short-term sleep group was more easily controlled after treatment with drugs for sleep regulation and basic antihypertensive drugs (p <0.05). The blood pressure level in patients with combined SARS-CoV-2 infection and hypertension urgencies was higher in those with a shorter duration of daily sleep, and also more difficult to control in Fangcang shelter hospital. Drug therapy for sleep regulation should be administered early to obtain sufficient blood pressure control effects.

DAYTIME SUPINE BLOOD PRESSURE NORMALIZED BY 24-HOUR VALUES INDEPENDENTLY PREDICTS FUNCTIONAL OUTCOME AFTER ISCHEMIC STROKE

Objective: Blood pressure (BP) after ischemic stroke (IS) may follow various patterns. Post-event acute BP alterations mirror both stroke and patient characteristics, and resolve over time, yet their clinical significance is low or uncertain. Whether individual BP variations, based on a single standardized measurement normalized by a background BP course, have a distinct significance for stroke outcome remains unknown. We hypothesized that the BP difference index (BPD) between daytime supine resting and a series of surrounding BP values (daytime, 24-hour (24h)) in the subacute phase of IS is associated with functional outcome. Design and method: we included 131 IS patients [age 60.8 ± 12.5 years, median (NIHSS) score 5 (3-8)]. Office BP measurements and continuous 24-hour BP monitoring were performed on day 7 after stroke onset. The daytime period was defined as the interval from 6 a.m. to 10 p.m. Functional outcome was evaluated 90 days after stroke using the modified Rankin Scale (mRS) with an mRS score of 3 to 6 (dependency or death) considered as a poor outcome. Results: In a univariate analysis, high BPD was significantly associated with a poor stroke outcome (p = 0.001, 0.003, and 0.002 for systolic, diastolic, and mean BP, respectively, irrespective of the normalization subperiod (daytime, 24h). In a multivariate analysis, the predictive value of BPD remained significant only for systolic BP [SBP] normalized by daytime or 24h mean (OR, 1.06; 95% CI, 1.01-1.11; p = 0.02) after adjustment for covariates. Moreover, the relationship was stronger in a subgroup of patients able to walk independently (mRS 0-2) on day 7 after stroke onset (adjusted OR, 1.08; 95% CI, 1.01-1.17; p = 0.049 for SBP normalized by daytime or adjusted OR, 1.09; 95% CI, 1.01-1.18; p = 0.03 for SBP normalized by 24h mean). Conclusions: We found that the higher difference between supine resting and daytime or diurnal mean BP in patients in the subacute phase of ischemic stroke is independently associated with a poor outcome. This BP index might be useful in clinical practice, including therapeutic decisions, but needs broader studies in patient populations of stroke subtypes.

Continuous cuffless blood pressure monitoring using photoplethysmography-based PPG2BP-net for high intrasubject blood pressure variations

Continuous, comfortable, convenient (C3), and accurate blood pressure (BP) measurement and monitoring are needed for early diagnosis of various cardiovascular diseases. To supplement the limited C3 BP measurement of existing cuff-based BP technologies, though they may achieve reliable accuracy, cuffless BP measurement technologies, such as pulse transit/arrival time, pulse wave analysis, and image processing, have been studied to obtain C3 BP measurement. One of the recent cuffless BP measurement technologies, innovative machine-learning and artificial intelligence-based technologies that can estimate BP by extracting BP-related features from photoplethysmography (PPG)-based waveforms have attracted interdisciplinary attention of the medical and computer scientists owing to their handiness and effectiveness for both C3 and accurate, i.e., C3A, BP measurement. However, C3A BP measurement remains still unattainable because the accuracy of the existing PPG-based BP methods was not sufficiently justified for subject-independent and highly varying BP, which is a typical case in practice. To circumvent this issue, a novel convolutional neural network(CNN)- and calibration-based model (PPG2BP-Net) was designed by using a comparative paired one-dimensional CNN structure to estimate highly varying intrasubject BP. To this end, approximately 70%, 20%, and 10% of 4185 cleaned, independent subjects from 25,779 surgical cases were used for training, validating, and testing the proposed PPG2BP-Net, respectively and exclusively (i.e., subject-independent modelling). For quantifying the intrasubject BP variation from an initial calibration BP, a novel ‘standard deviation of subject-calibration centring (SDS)’ metric is proposed wherein high SDS represents high intrasubject BP variation from the calibration BP and vice versa. PPG2BP-Net achieved accurately estimated systolic and diastolic BP values despite high intrasubject variability. In 629-subject data acquired after 20 minutes following the A-line (arterial line) insertion, low error mean and standard deviation of 0.209pm 7.509 and 0.150pm 4.549;textrm{mmHg} for highly varying A-line systolic and diastolic BP values, respectively, where their SDSs are 15.375 and 8.745. This study moves one step forward in developing the C3A cuffless BP estimation devices that enable the push and agile pull services.

Noninvasive continuous arterial pressure monitoring shortens atrial fibrillation ablation procedural duration

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Transcatheter atrial fibrillation (AF) ablation is in most centres commonly carried out with continuous invasive radial arterial blood pressure (BP) monitoring. Novel devices enable continuous non-invasive BP monitoring, with acceptable agreement and optimal safety profile when compared to standard of care invasive BP monitoring, leading to improved patient comfort in the electrophysiology lab. Purpose Aim of the study was to assess in terms of procedural efficiency continuous non-invasive BP monitoring during transcatheter atrial fibrillation ablation. Methods We prospectively enrolled 42 consecutive patients (age 61±9 years, 80% male) undergoing transcatheter AF ablation (60% paroxysmal, 40% persistent) at our centre undergoing AF ablation with continuous BP measurement using a non-invasive finger volume clamp device. We then compared them with an historical cohort of 42 consecutive patients undergoing AF ablation (62% paroxysmal, 38% persistent) with standard of care invasive BP monitoring with a radial cannula. We compared the two groups in terms of total procedural duration (in and out from the EP lab). Results Mean total procedural duration was 165,29±54,95 minutes in the non-invasive group and 196,55±46,67 minutes in the invasive group (P=0,006). Conclusion In patients undergoing AF ablation, non-invasive finger volume-clamp continuous BP monitoring allowed for a significant reduction of total procedural duration when compared to standard of care invasive BP monitoring. Larger studies are needed to confirm these results.

Piezoelectric Metamaterial Blood Pressure Sensor

Continuous blood pressure monitoring allows for detecting the early onset of cardiovascular disease and assessing personal health status. Conventional piezoelectric blood pressure monitoring techniques have the ability to sense biosignals due to their good dynamic responses but have significant drawbacks in terms of power consumption, which limits the operation of blood pressure sensors. Although piezoelectric materials can be used to enhance the self-powered blood pressure sensor responses, the structure of the piezoelectric element can be modified to achieve a higher output voltage. Here, a structural study on piezoelectric metamaterials in blood pressure sensors is demonstrated, and output voltages are computed and compared to other architectures. Next, a Bayesian optimization framework is defined to get the optimal design according to the metamaterial design space. Machine learning algorithms were used for applying regression models to a simulated dataset, and a 2D map was visualized for key parameters. Finally, a time-dependent blood pressure was applied to the inner surface of an artery vessel inside a 3D tissue skin model to compare the output voltage for different metamaterials. Results revealed that all types of metamaterials can generate a higher electric potential in comparison to normal square-shaped piezoelectric elements. Bayesian optimization showed that honeycomb metamaterials had the optimal performance in generating output voltage, which was validated according to regression model analysis resulting from machine learning algorithms. The simulation of time-dependent blood pressure in a 3D skin tissue model revealed that the design suggested by the Bayesian optimization process can generate an electric potential more than two times greater than that of a conventional square-shaped piezoelectric element.

Noninvasive finger plethysmography for continuous blood pressure monitoring in patients with left ventricular assist device.

Accurate blood pressure (BP) measurement remains challenging in patients with HeartMate 3™ left ventricular assist devices (HM3 LVADs). The Finapres® NOVA is a promising non-invasive continuous BP monitor that uses the volume clamp method via a finger cuff, so here we aimed to validate the instrument in HM3 patients. In a single-center cohort, BP was monitored in 15 patients within 72 h following HM3 implantation. A radial artery catheter quantified arterial blood pressure (ABP), while the NOVA measured finger arterial pressure (fiAP) and reconstructed brachial artery pressure (reBAP). Waveforms were recorded for 10 min, and mean values were calculated in 15-s intervals. fiAP and ABP were moderately correlated during both the first (ICC 0.61, p = 0.04) and final measurements (ICC 0.66, p = 0.03). reBAP and ABP were strongly correlated during both the first (ICC 0.81, p = 0.002) and final measurements (ICC 0.83, p = 0.001). Both NOVA-derived values may underestimate low BP values while overestimating relatively high BP values. The reBAP was within 5 mm Hg of the ABP in 40% of patients (and within 10 mm Hg in 67%). This pilot represents the first evidence in support of the Finapres® NOVA for non-invasive BP measurement in select patients with HM3 LVADs. The instrument may provide useful data during BP medication adjustments or pump titration, but despite the correlation between the non-invasive reBAP and invasive ABP, individual-level inaccuracy may be clinically meaningful. Further investigation is needed to clarify these limitations and optimize accuracy before widespread adoption in this unique patient population.