Continuous Blood Pressure Monitoring Research Articles

Novel metrics for tracking blood pressure changes incontinuous cuffless blood pressure estimations

Recent studies revealed the importance of tracking continuous blood pressure (BP) changes in monitoring and controlling hypertension and diagnosing cardiovascular diseases. However, current evaluation protocols utilize distance measures as primary metrics, which cannot properly evaluate the ability of the estimation model to track BP changes. This paper proposes a comprehensive evaluation framework which evaluates the distance and trend similarity metrics, and the composite metric of both between the reference and estimated BPs. The results of applying both widely used conventional metrics and the new proposed metrics for BP estimations are demonstrated in an example of comparing the reference with a set of different BP estimations. Then, the metrics are applied to BP estimations obtained using state-of-the-art (SOTA) algorithms. It is shown that even though SOTA algorithms have a low mean and standard deviation of absolute difference, they are not capable of tracking short-term blood pressure changes. Additionally, the proposed metrics are normalized metrics and range from -1 to 1, making them intuitively interpretable, similar to well-known correlation coefficients. Therefore, we suggest that the proposed evaluation framework should be used regularly in evaluating continuous BP monitoring systems.

Personalized blood pressure estimation using multiview fusion information of wearable physiological signals and transfer learning

Continuous blood pressure (BP) monitoring is crucial for individual health management, yet the significant inter-individual variations among patients pose challenges to achieving precision medicine. In response to this issue, we propose a parallel cross-hybrid architecture that integrates a convolutional neural network backbone and a Mix-Transformer backbone. This model, grounded in multi-view physiological signals and personalized fine-tuning strategies, aims to estimate BP, facilitating the capture of physiological information across diverse receptive fields and enhancing network expressive capabilities. Our proposed architecture exhibits superior performance in estimating systolic blood pressure and diastolic blood pressure, with average absolute errors of 3.94 mmHg and 2.24 mmHg, respectively. These results surpass existing baseline models and align with the standards set by the British Hypertension Society, the Association for the Advancement of Medical Instrumentation, and the Institute of Electrical and Electronics Engineers for BP measurement. Additionally, this study explores a personalized model fine-tuning strategy by adjusting specific layers and incorporating individual information, presenting an optimal solution. The model's generalization ability is validated through transfer learning across databases (public and self-made). To enhance the proposed architecture's usability in wearable devices, this study employs a knowledge distillation strategy for model lightweighting, with preliminary application in our designed real-time BP estimation system. This study provides an efficient and accurate solution for personalized BP estimation, exhibiting broad potential applications.

Healthcare with Wearable Devices and Machine Learning

As health management continues to grow in importance globally, driven by the quest for improved health outcomes, longevity, and personalized care, machine learning (ML) has become a popular technique for detecting and analyzing health indicators, playing an essential role in multiple areas of health detection, such as continuous heart and blood pressure monitoring, blood sugar tracking for diabetics, sleep analysis to improve sleep quality, and even disease prediction. With wearable devices, a particular scale of health detection data has been accumulated at this stage. With this data, machine learning can be predictive analytics to assess real-time health conditions, enabling early intervention and personalized treatment plans. However, data quality remains the most critical issue for machine learning-based health detection systems, as inaccuracies in sensor readings can lead to misdiagnoses or incorrect treatment decisions. In addition, privacy concerns are significant, as the sensitive health information collected by these devices requires strong security measures to protect users’ data. Moreover, the interpretability of machine learning algorithms, especially those involving deep learning, can be limited, hindering clinicians’ understanding and trust. This paper addresses these challenges by providing a comprehensive overview of relevant data sets used in health monitoring and examining the latest machine learning algorithms tailored for wearables-based health detection. It further delves into the current limitations and challenges facing this emerging field, providing insights into potential solutions and future directions for research and development.

Peripheral Use of Vasopressors in Shock: Clinical Considerations and Recommendations for Use in Obstetrics.

This study aimed to evaluate the safety of peripheral administration of vasopressor agents among patients with circulatory shock. We reviewed the published literature evaluating the use of peripheral norepinephrine in patients with shock and proposed a protocol for use in labor and delivery units. Peripheral administration of norepinephrine is a safe and potentially lifesaving intervention for patients in labor and delivery with extremely low complication rates. Adoption of a protocol for peripheral administration of vasopressors in labor and delivery is safe and may prevent life threatening delays in hemodynamic resuscitation. · Administering vasopressors through a peripheral line is safe and helps avoid delays in care.. · An established protocol is essential for the safe peripheral administration of vasopressors.. · Understanding continuous blood pressure monitoring is crucial for managing critically ill patients..

Implantable small ultra-wideband circularly polarized antenna design for continuous blood pressure monitoring

This paper presents a miniaturized circularly polarized (CP) implantable antenna Ultra-wide bandwidth for continuous blood pressure monitoring. The miniature and CP of the antenna are gained by using a new slot method. The symmetry slots in the radiation patch, two T-shape slots in the GND, coupled with the use of a short pin make the designed antenna with good physical and radiation properties. In simulation, the fractional effective axial ratio bandwidth is 23.6% (2.36–2.94 GHz), and the peak gain is − 28.9 dBi. Its total size is only 17.78 mm3 (0.056 × 0.04 × 0.004 λ03), which size is smaller compared to other antennas with similar performance. A prototype is fabricated and measured. The experimental results are in good agreement with the simulation results. And, the radiation patterns have good symmetry both in the simulation and measurement. In addition, the maximum SAR value is in accordance with the IEEE standard safety guidelines (IEEE C95.1-2019).

Cuffless Wearable Sphygmomanometers Using Dual Digital Optical Frequency Combs in Chalcogenide Chips

AbstractSphygmomanometers typically use a rubber cuff around the upper arm to measure blood pressure, but this method can be uncomfortable. Thus, cuffless sphygmomanometers for continuous blood pressure monitoring in emergencies and healthcare are desirable. While electrical and optical blood pressure sensors offer high sensitivity, they often face issues like limited pressure range, temperature drift, slow response, and wearability problems. To tackle these limitations, the study designs a unique cuffless wearable blood pressure sensor (12 mm × 2 mm × 0.5 mm) featuring two original components: a GeSbS/AsS chalcogenide dual‐microring chip for high sensitivity, and a dual digital optical frequency comb (DDOFC) system for fast response and cost‐effective detection. The sensor is comparable to reported electrical and optical blood pressure sensors in its detection limit (23 Pa) but has a ten‐times faster response rate (2 kHz), a 1000‐times longer stable operation (>4.3 × 107 cycles), and a well‐compensated temperature drift (<0.012 pm/°C) that eliminates the need for temperature control. This innovation shows promise for wearable electronics and mobile healthcare, enabling the capture of critical cardiovascular details for applications like in‐surgery monitoring, orthostatic hypotension studies, and early detection of myocardial ischemia and strokes.

Carotid sinus massage in clinical practice: the Six-Step-Method.

Carotid sinus massage (CSM) as integral part of cardiovascular autonomic testing is indicated in all patients > 40 years with syncope of unknown origin and suspected reflex mechanism. However, large practice variation exists in performing CSM that inevitably affects the positivity rate of the test and may result in an inaccurate diagnosis in patients with unexplained syncope. Even though CSM was introduced into medical practice more than 100 years ago, the method of performing CSM is still largely operator- and centre-dependent, while in many places, the test has been entirely abandoned. Here, we describe a standardized protocol on how to perform CSM, which basic monitoring equipment is necessary and why CSM is a safe procedure to perform. Our aim is to create a uniform approach to perform CSM. The new proposed algorithm, the Six-Step-Method, includes: (i) check history for exclusion CSM; (ii) turn head slightly contralaterally and posterior (see also explanatory video and poster provided as Supplementary material; (iii) palpation to identify carotid sinus location; (iv) massage for 10 s; (v) monitoring of blood pressure and heart rate to assess of the haemodynamic response type; and (vi) include time intervals between subsequent massages. Carotid sinus massage should be performed on both the left and right and in the supine and upright position. The recommended equipment to perform CSM consists of: (i) a tilt table in order to perform CSM in supine and standing position, (ii) a continuous blood pressure monitor or cardiac monitor, and (iii) at least two persons.

Wearable cuffless blood pressure monitoring devices: a commentary.

Hypertension is a growing public challenge as a leading risk factor for cardiovascular disease and all-cause mortality. Reducing overall cardiovascular risk through early screening, initiation of treatment and ongoing monitoring remains a priority in the comprehensive management of hypertension and its complications. Community nurses are ideally positioned to play a crucial role in the early detection of hypertension and providing support for its management. Wearable cuffless devices have the potential for continuous remote blood pressure monitoring. However, there is not enough literature on the validity and usability of wearable cuffless blood pressure devices to justify their use in clinical practice. This commentary critically appraises a systematic review designed to assess the validity, features and clinical usability of wearable cuffless devices, and expands on its findings and their relevance to community nursing and future research.

Traditional Chinese Medicine (TCM)-Inspired Fully Printed Soft Pressure Sensor Array with Self-Adaptive Pressurization for Highly Reliable Individualized Long-Term Pulse Diagnostics.

Reliable, non-invasive, continuous monitoring of pulse and blood pressure is essential for the prevention and diagnosis of cardiovascular diseases. However, the pulse wave varies drastically among individuals or even over time in the same individual, presenting significant challenges for the existing pulse sensing systems. Inspired by pulse diagnosis methods in traditional Chinese medicine (TCM), this work reports a self-adaptive pressure sensing platform (PSP) that combines the fully printed flexible pressure sensor array with an adaptive wristband-style pressure system can identify the optimal pulse signal. Besides the detected pulse rate/width/length, "Cun, Guan, Chi" position, and "floating, moderate, sinking" pulse features, the PSP combined with a machine learning-based linear regression model can also accurately predict blood pressure such as systolic, diastolic, and mean arterial pressure values. The developed diagnostic platform is demonstrated for highly reliable long-term monitoring and analysis of pulse and blood pressure across multiple human subjects over time. The design concept and proof-of-the-concept demonstrations also pave the way for the future developments of flexible sensing devices/systems for adaptive individualized monitoring in the complex practical environments for personalized medicine, along with the support for the development of digital TCM.

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.

Comparison of the ClearSight™ finger cuff monitor versus invasive arterial blood pressure measurement in elective cardiac surgery patients: a prospective observational study.

To determine the acceptability of the ClearSight™ system (Edwards Lifesciences Corp., Irvine, CA, USA) for continuous blood pressure monitoring during elective cardiac surgery compared with arterial catheterization. We enrolled 30 patients undergoing elective cardiac surgery in a prospective observational study. Blood pressure measurements were recorded every 10 sec intraoperatively. We determined agreement based on the Association for the Advancement of Medical Instrumentation (AAMI) recommendations. Statistical analysis included fixed bias (difference of measurements between methods), percentage error (accuracy between ClearSight measurement and expected measurement from arterial line), and interchangeability (ability to substitute ClearSight monitor without effecting overall outcome of analysis). We used a paired samples t test to compare the time required for placing each monitor. We found fixed bias in the differences between the ClearSight monitor and invasive arterial blood pressure measurement in systolic blood pressure (SBP; mean difference, 8.7; P < 0.001) and diastolic blood pressure (DBP; mean difference, -2.2; P < 0.001), but not in mean arterial pressure (MAP; mean difference, -0.5; P < 0.001). Bland-Altman plots showed that the means of the limits of agreement were greater than 5mm Hg for SBP, DBP, and MAP. The percentage errors for SBP, DBP, and MAP were lower than the cutoff we calculated from the invasive arterial blood pressure measurements. Average interchangeability rates were 38% for SBP, 50% for DBP, and 50% for MAP. Placement of the ClearSight finger cuff was significantly faster compared with arterial catheterization (mean [standard deviation], 1.7 [0.6] min vs 5.6 [4.1] min; P < 0.001). In this prospective observational study, we did not find the ClearSight system to be an acceptable substitute for invasive arterial blood pressure measurement in elective cardiac surgery patients according to AAMI guidelines. Nevertheless, based on statistical standards, there is evidence to suggest otherwise. ClinicalTrials.gov ( NCT05825937 ); first submitted 11 April 2023.

Continuous blood pressure monitoring based on transformer encoders and stacked attention gated recurrent units

Continuous blood pressure monitoring (CBPM) is critical to support the accurate prevention and reliable treatment of cardiovascular diseases. To achieve efficient multi-information interaction and further improve the monitoring performance, this research proposes an intelligent model based on transformer encoders and stacked attention gated recurrent units (TE-SAGRU) for CBPM. Long-term multi-source feature sequences with rich information are initially extracted from photoplethysmography (PPG) and electrocardiography (ECG) signals. The paralleled transformer encoders are constructed for different source feature sequences to obtain high-level feature representations and preserve respective long-term independence. The multiple stacked attention gated recurrent units are cross-connected for multi-interactive feature fusion and promoting complementarity effects of multi-source features on CBPM. Comprehensive comparison experiments are carried out to validate the effectiveness of the TE-SAGRU model, using the dataset with 1000 subjects derived from the MIMIC-III database. The continuous monitoring errors of the TE-SAGRU model for systolic blood pressure (SBP) and diastolic blood pressure (DBP) are 3.91 ± 5.65 mmHg and 2.29 ± 3.01 mmHg. The monitored results pass the requirement of the Association for the Advancement of Medical Instrumentation (AAMI) standard and achieve Grade A of the British Hypertension Society (BHS) protocol.

A Pilot and Feasibility Study of Continuous Cardiac Output and Blood Pressure Monitoring during Intermittent Hemodialysis

Introduction: Hypotension is common during intermittent hemodialysis (IHD) and may be due to a decreased cardiac index (CI). However, no study has simultaneously and continuously measured CI and mean arterial pressure (MAP) to understand the prevalence, severity, and duration of CI decreases or relate them to MAP, blood volume (BV), and net ultrafiltration (NUF) rate. Methods: In a prospective, pilot and feasibility investigation, we studied 10 chronic IHD patients. We used the ClearSight System™ to continuously monitor CI and MAP; the CRIT-LINE®IV monitor to detect BV changes and collected data on NUF rate. Results: Device tolerance and compliance were 100%. All patients experienced at least ≥1 episode of severe CI decrease (>25% from baseline), with a median duration of 24 min (IQR 6–87) and of 68 min [14–106] for moderate decreases (>15% but ≤25% from baseline). Eight patients experienced a low CI state (<2.2 L/min/m2). The lowest CI was 0.9 L/min/m2 with a concomitant MAP of 94 mm Hg. When the fall in CI was severe, MAP increased in 58% of cases and remained stable in 28%. Overall, CI decreased by −0.55 L/min/m2 when BV decrease was moderate versus mild (p < 0.001) and by −0.8 L/min/m2 when NUF rate was high versus low (p < 0.001). Conclusion: Continuous CI monitoring is feasible in IHD and shows frequent moderate-severe CI decreases, sometimes to low CI state levels. Such decreases are typically associated with markers of decreased intravascular volume status but not with a decrease in MAP, implying marked vasoconstriction.

Abstract P444: Radial pulse wave velocity measurement method with dual ultrasound probe for low power wearables

Background: Wearables for continuous blood pressure monitoring hold the promise to drastically improve hypertension management, but current solutions still lack the required accuracy. Ultrasounds might be able to overcome this limitation because they can measure quantitative parameters highly correlated with blood pressure, such as artery diameter, its motion over the cardiac cycle (AWM) and local pulse wave velocity (PWV). Here we validate radial PWV measurement with an ultrasound method that can be integrated in low power wearables. Methods: The study was conducted on 8 healthy subjects at rest. The ultrasound scan was performed on the left arm with a research scanner and two linear probes held at a fixed distance and used to image two transversal sections of the radial artery at 11.5 kHz for 10 seconds. The first image of each section is segmented to identify the artery walls and AWM is reconstructed by tracking the phase of the wall echo. PWV is extracted from the delay of artery wall motion waveforms on the 2 sections. Reference values of carotid-radial PWV were acquired with Diatecne PulsePen ETT immediately after the ultrasound acquisition on the same arm. Results: The estimate and accuracy of the local radial PWV of proposed ultrasound method is in agreement with the reference carotid-radial PWV obtained with the tonometer. The accuracy of the methods is estimated from the beat-to-beat variability of the delays between the waves used for the estimates. Conclusions: The proposed method allows to measure the radial pulse wave within shorter distances compatible with integration in wearables. Leveraging TDK ultrasound MEMS platform, this paves the route for low power wearable for continuous cardio-vascular monitoring.

Reliability of beat-to-beat blood pressure variability in older adults

Blood pressure variability (BPV) is emerging as an important risk factor across numerous disease states, including cerebrovascular and neurodegenerative disease in older adults. However, there is no current consensus regarding specific use cases for the numerous available BPV metrics. There is also little published data supporting the ability to reliably measure BPV across metrics in older adults. The present study derived BPV metrics from continuous beat-to-beat blood pressure monitoring data. Two sequential 7 min waveforms were analyzed. Absolute and relative reliability testing was performed. Differences between antihypertensive medication users and non-users on BPV metric reliability was also assessed. All sequence and dispersion based BPV metrics displayed good test–retest reliability. A measure of BP instability displayed only moderate reliability. Systolic and diastolic average real variability displayed the highest levels of reliability at ICC = 0.87 and 0.82 respectively. Additionally, systolic average real variability was the most reliable metric in both the antihypertensive use group, and the no antihypertensive use group. In conclusion, beat-to-beat dispersion and sequence-based metrics of BPV can be reliably obtained in older adults using noninvasive continuous blood pressure monitoring. Average real variability may be the most reliable and specific beat-to-beat blood pressure variability metric due to its decreased susceptibility to outliers and low frequency blood pressure oscillations.

Beat-to-beat blood pressure variability, hippocampal atrophy, and memory impairment in older adults.

Visit-to-visit blood pressure variability (BPV) predicts age-related hippocampal atrophy, neurodegeneration, and memory decline in older adults. Beat-to-beat BPV may represent a more reliable and efficient tool for prospective risk assessment, but it is unknown whether beat-to-beat BPV is similarly associated with hippocampal neurodegeneration, or with plasma markers of neuroaxonal/neuroglial injury. Independently living older adults without a history of dementia, stroke, or other major neurological disorders were recruited from the community (N = 104; age = 69.5 ± 6.7 (range 55-89); 63% female). Participants underwent continuous blood pressure monitoring, brain MRI, venipuncture, and cognitive testing over two visits. Hippocampal volumes, plasma neurofilament light, and glial fibrillary acidic protein levels were assessed. Beat-to-beat BPV was quantified as systolic blood pressure average real variability during 7-min of supine continuous blood pressure monitoring. The cross-sectional relationship between beat-to-beat BPV and hippocampal volumes, cognitive domain measures, and plasma biomarkers was assessed using multiple linear regression with adjustment for demographic covariates, vascular risk factors, and average systolic blood pressure. Elevated beat-to-beat BPV was associated with decreased left hippocampal volume (P = .008), increased plasma concentration of glial fibrillary acidic protein (P = .006), and decreased memory composite score (P = .02), independent of age, sex, average systolic blood pressure, total intracranial volume, and vascular risk factor burden. In summary,beat-to-beat BPV is independently associated with decreased left hippocampal volume, increased neuroglial injury, and worse memory ability. Findings are consistent with prior studies examining visit-to-visit BPV and suggest beat-to-beat BPV may be a useful marker of hemodynamic brain injury in older adults.

Continuous non-invasive vs. invasive arterial blood pressure monitoring during neuroradiological procedure: a comparative, prospective, monocentric, observational study

BackgroundIn the perioperative setting, the most accurate way to continuously measure arterial blood pressure (ABP) is using an arterial catheter. Surrogate methods such as finger cuff have been developed to allow non-invasive measurements and are increasingly used, but need further evaluation. The aim of this study is to evaluate the accuracy and clinical concordance between two devices for the measurement of ABP during neuroradiological procedure.MethodsThis is a prospective, monocentric, observational study. All consecutive patients undergoing a neuroradiological procedure were eligible. Patients who needed arterial catheter for blood pressure measurement were included. During neuroradiological procedure, ABP (systolic, mean and diatolic blood pressure) was measured with two different technologies: radial artery catheter and Nexfin. Bland-Altman and error grid analyses were performed to evaluate the accuracy and clinical concordance between devices.ResultsFrom March 2022 to November 2022, we included 50 patients, mostly ASA 3 (60%) and required a cerebral embolization (94%) under general anaesthesia (96%). Error grid analysis showed that 99% of non-invasive ABP measures obtained with the Nexfin were located in the risk zone A or B. However, 65.7% of hypertension events and 41% of hypotensive events were respectively not detected by Nexfin. Compared to the artery catheter, a significant relationship was found for SAP (r2 = 0.78) and MAP (r2 = 0.80) with the Nexfin (p < 0.001). Bias and limits of agreement (LOA) were respectively 9.6 mmHg (− 15.6 to 34.8 mmHg) and − 0.8 mmHg (− 17.2 to 15.6 mmHg), for SAP and MAP.ConclusionsNexfin is not strictly interchangeable with artery catheter for ABP measuring. Further studies are needed to define its clinical use during neuroradiological procedure.Trial registrationClinicaltrials.gov, registration number: NCT05283824.

Impact of procedural handling on the physiological effects of alfaxalone anaesthesia in the ball python (Python regius)

To describe the cardiovascular changes following intramuscular (handled) and intravascular (undisturbed, via intraarterial catheter) alfaxalone administration, we studied 20 healthy ball pythons (Python regius) in a randomised, prospective study. The pythons were instrumented with occlusive arterial catheters to facilitate undisturbed, continuous monitoring of heart rate and blood pressure. Six pythons were administered intramuscular (IM) saline, followed by 20 mg/kg IM alfaxalone, and were manually restrained for both injections. Six pythons received intraarterial (IA) saline, followed by 10 mg/kg IA alfaxalone, and remained undisturbed for both injections. Arterial blood samples were taken at 0, 12 and 60 min post-injection, and heart rate and blood pressure were recorded for 60 min. The remaining eight snakes received 20 mg/kg IM or 10 mg/kg IA alfaxalone (n = 4 per treatment) and were not handled for intubation 10 min post-injection, to examine the effects of handling during anaesthesia. IM administration of 20 mg/kg alfaxalone or an equivalent volume of saline elicited a profound tachycardia and hypertension, which recovered to resting values after 20 min. However, when 10 mg/kg alfaxalone or saline were injected IA, mild hypotension and a lower magnitude tachycardia occurred. Arterial PCO2 and PO2, pH and lactate concentrations did not change following IA alfaxalone, but an acidosis was observed during IM alfaxalone anaesthesia. There were no significant changes in plasma catecholamines and corticosterone among treatments. Handling for injection and during anaesthesia associated with intubation significantly affects cardiovascular parameters, whereas alfaxalone per se only elicits minor changes in cardiovascular physiology.

Continuous blood pressure prediction system using Conv-LSTM network on hybrid latent features of photoplethysmogram (PPG) and electrocardiogram (ECG) signals

Continuous blood pressure (BP) monitoring is essential for managing cardiovascular disease. However, existing devices often require expert handling, highlighting the need for alternative methods to simplify the process. Researchers have developed various methods using physiological signals to address this issue. Yet, many of these methods either fall short in accuracy according to the BHS, AAMI, and IEEE standards for BP measurement devices or suffer from low computational efficiency due to the complexity of their models. To solve this problem, we developed a BP prediction system that merges extracted features of PPG and ECG from two pulses of both signals using convolutional and LSTM layers, followed by incorporating the R-to-R interval durations as additional features for predicting systolic (SBP) and diastolic (DBP) blood pressure. Our findings indicate that the prediction accuracies for SBP and DBP were 5.306 ± 7.248 mmHg with a 0.877 correlation coefficient and 3.296 ± 4.764 mmHg with a 0.918 correlation coefficient, respectively. We found that our proposed model achieved a robust performance on the MIMIC III dataset with a minimum architectural design and high-level accuracy compared to existing methods. Thus, our method not only meets the passing category for BHS, AAMI, and IEEE guidelines but also stands out as the most rapidly accurate deep-learning-based BP measurement device currently available.

Nursing Interventions in Surgical Patients with Hypertension: Strategies for Optimal Perioperative Blood Pressure Management

This study explores nursing interventions for surgical patients with hypertension, emphasizing strategies for optimal perioperative blood pressure management. Hypertension significantly increases surgical risk, necessitating tailored perioperative care. The objective of this research is to identify and evaluate effective nursing interventions that mitigate these risks and improve patient outcomes. A systematic review was conducted, including randomized controlled trials, cohort studies, and clinical guidelines from 2010 to 2023. The analysis focused on preoperative, intraoperative, and postoperative phases, assessing interventions such as medication management, lifestyle modification counseling, patient education, and monitoring protocols. The findings reveal that preoperative optimization of blood pressure through medication adherence and lifestyle adjustments is crucial. Education about the importance of blood pressure control and adherence to prescribed antihypertensive regimens significantly reduces perioperative complications. Intraoperative strategies include continuous blood pressure monitoring and the administration of antihypertensive agents as needed to maintain stability. Postoperative care focuses on regular blood pressure monitoring, early identification of complications, and patient education to ensure long-term management. The study concludes that a multidisciplinary approach involving nurses, surgeons, and anesthesiologists is essential for effective perioperative management in hypertensive patients. Continuous patient education and engagement in their care, combined with vigilant monitoring and timely intervention, significantly reduce adverse outcomes. These findings underscore the importance of comprehensive, patient-centered nursing interventions in enhancing surgical outcomes for hypertensive patients. Future research should focus on developing standardized protocols and exploring the long-term effects of these interventions on surgical morbidity and mortality.