Real-time Blood Pressure Monitoring Research Articles

Using Behavioural Biometrics and Machine Learning in Smart Gadgets for Continuous User Authentication Purposes

In the ever-evolving realm of technology, the identification of human activities using intelligent devices such as smartwatches, fitness bands, and smartphones has emerged as a crucial area of study. These devices, equipped with inertial sensors, gather a wealth of data and provide insights into users' movements and behaviors. These data not only serve practical purposes, but also hold significant implications for domains such as healthcare and fitness tracking. Traditionally, these devices have been employed to monitor various health metrics such as step counts, calorie expenditure, and real-time blood pressure monitoring. However, recent research has shifted its focus to leveraging the data collected by these sensors for user authentication purposes. This innovative approach involves the utilization of Machine Learning (ML) models to analyze the routine data captured by sensors in smart devices employing ML algorithms, which can recognize and authenticate users based on their unique movement patterns and behaviors. This introduces a paradigm shift from traditional one-time authentication methods to continuous authentication, adding an extra layer of security to protect users against potential threats. Continuous authentication offers several advantages over its conventional counterparts. First, it enhances security by constantly verifying a user's identity through their interaction with the device, thereby mitigating the risk of unauthorized access. Second, it provides a seamless and nonintrusive user experience, eliminating the need for repetitive authentication prompts. Moreover, it offers robust protection against various threats such as identity theft, unauthorized access, and device tampering. The application of continuous authentication extends beyond individual devices and encompasses interconnected systems and networks. This holistic approach ensures a comprehensive security across digital platforms and services. The experiments demonstrate that the logistic regression model achieves an accuracy of 82.32% on the test dataset, highlighting its robustness for binary classification tasks. Additionally, the random forest model outperforms with a 92.18% accuracy, emphasizing its superior capability in handling complex feature interactions. In the study, the sequential neural network achieved an accuracy of 92% on the HAR dataset, outperforming traditional machine learning models by a significant margin. The model also demonstrated robust generalization capabilities with a minimal drop in performance across various cross-validation folds.

Non-invasive continuous blood pressure prediction based on ECG and PPG fusion map.

To achieve real-time blood pressure monitoring, a novel non-invasive method is proposed in this article. Electrocardiographic (ECG) and pulse wave signals (PPG) are fused from a multi-omics signal-level perspective. A physiological signal fusion matrix and fusion map, which can estimate the blood pressure of blood loss(BPBL), are constructed. The results demonstrate the efficacy of the fusion map model, with correlation values of 0.988 and 0.991 between the estimated BPBL and the true systolic blood pressure (SBP) and diastolic blood pressure (DBP), respectively. The root mean square errors for SBP and DBP were 3.21mmHg and 3.00mmHg, respectively. The model validation showed that the fusion map method is capable of simultaneous highlighting of the respective characteristics of ECG and PPG and their correlation, improving the utilization of the information and the accuracy of BPBL. This article validates that physiological signal fusion map can effectively improve the accuracy of BPBL estimation and provides a new perspective for the field of physiological information fusion.

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

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

Blood Pressure Sensors: Materials, Fabrication Methods, Performance Evaluations and Future Perspectives.

Advancements in materials science and fabrication techniques have contributed to the significant growing attention to a wide variety of sensors for digital healthcare. While the progress in this area is tremendously impressive, few wearable sensors with the capability of real-time blood pressure monitoring are approved for clinical use. One of the key obstacles in the further development of wearable sensors for medical applications is the lack of comprehensive technical evaluation of sensor materials against the expected clinical performance. Here, we present an extensive review and critical analysis of various materials applied in the design and fabrication of wearable sensors. In our unique transdisciplinary approach, we studied the fundamentals of blood pressure and examined its measuring modalities while focusing on their clinical use and sensing principles to identify material functionalities. Then, we carefully reviewed various categories of functional materials utilized in sensor building blocks allowing for comparative analysis of the performance of a wide range of materials throughout the sensor operational-life cycle. Not only this provides essential data to enhance the materials’ properties and optimize their performance, but also, it highlights new perspectives and provides suggestions to develop the next generation pressure sensors for clinical use.

Noninvasive blood pressure estimation with peak delay of different pulse waves

In this article, we discuss the validity of noninvasive continuous blood pressure estimation with two different types of peripheral pulse waves. Artery-blocking experiment shows that phase difference of two pulse waves at the same location is well related with blood pressure and blood flow fluctuation. Exercise-recovery experiment resulting from 16 subjects shows that phase difference varies with blood pressure with the correlation from 0.63 to 0.88 when blood pressure changes rapidly. Simulations based on a classic hemodynamic model verify the relationship between phase difference and blood pressure. However, phase difference is strongly correlated with smooth muscle state of the arterial wall as well. If smooth muscle information can be obtained by further study, phase difference can act as a promising approach to portable and wearable device for real-time blood pressure monitoring.

Temperature Compensated Fibre Bragg Grating Pressure Sensor for Ventricular Assist Devices.

Rotary blood pumps may be used as ventricular assist devices (VADs) to support patients with end-stage heart failure-'rotary VADs'. Clinically, rotary VADs are operated at a constant speed which is set manually. Due to inadequate haemodynamic monitoring equipment outside of the hospital setting, device speed remains the same for weeks or months at a time, leaving clinicians in the dark, and patients vulnerable to harmful over- or under-pumping events. Therefore, it would be beneficial to have an implantable sensor which can measure blood pressure at the rotary VAD inlet or outlet and detect the onset of adverse events. In this study, a temperature compensated fibre Bragg grating (FBG) based strain sensor which can be incorporated into a VAD and used for continuous, real-time blood pressure monitoring is investigated. Error in the pressure reading between the developed and reference sensor occurred due to changes in temperature. A generalised linear model was used to compensate for temperature related error between 35-39º. Without temperature compensation, the mean error in the pressure reading over the desired range of -25 to 150 mmHg was approximately ±5 mmHg. The temperature compensated mean error over the same range was less than ±2 mmHg. The compensation technique was effective over a wide range of temperatures and pressures, demonstrating the potential of the sensor for continuous real-time blood pressure monitoring.

Design of U-healthcare System for Real-time Blood Pressure Monitoring

Design of U-healthcare System for Real-time Blood Pressure Monitoring

A non-invasive approach to investigation of ventricular blood pressure using cardiac sound features

Heart sounds (HSs) are produced by the interaction of the heart valves, great vessels, and heart wall with blood flow. Previous researchers have demonstrated that blood pressure can be predicted by exploring the features of cardiac sounds. These features include the amplitude of the HSs, the ratio of the amplitude, the systolic time interval, and the spectrum of the HSs. A single feature or combinations of several features have been used for prediction of blood pressure with moderate accuracy.Experiments were conducted with three beagles under various levels of blood pressure induced by different doses of epinephrine. The HSs, blood pressure in the left ventricle and electrocardiograph signals were simultaneously recorded. A total of 31 records (18 262 cardiac beats) were collected. In this paper, 91 features in various domains are extracted and their linear correlations with the measured blood pressures are examined. These features are divided into four groups and applied individually at the input of a neural network to predict the left ventricular blood pressure (LVBP).The analysis shows that non-spectral features can track changes of the LVBP with lower standard deviation. Consequently, the non-spectral feature set gives the best prediction accuracy. The average correlation coefficient between the measured and the predicted blood pressure is 0.92 and the mean absolute error is 6.86 mmHg, even when the systolic blood pressure varies in the large range from 90 mmHg to 282 mmHg.Hence, systolic blood pressure can be accurately predicted even when using fewer HS features. This technique can be used as an alternative to real-time blood pressure monitoring and it has promising applications in home health care environments.

Elastomeric nanowire composite for flexible pressure sensors with tunable sensitivity

ABSTRACTFlexible pressure sensors can be applied to human–machine interfaces, next-generation touch interfaces for wearable displays, and real-time blood pressure monitoring. For these applications, pressure sensors must have high pressure sensitivity, flexibility, stability, and tunable sensitivity, like the human skin. Reported in this paper is a highly sensitive and flexible pressure sensor with tunable sensitivity. Silver-nanowires-embedded PDMS, the elastomeric nanowire composite, was integrated with a polymeric dielectric layer and a printed electrode to obtain a capacitive pressure sensor. By controlling the mixing ratio of the PDMS matrix of the nanowire composite, the pressure sensitivity of the sensor can be easily tuned. The sensor also showed high sensitivity (sensitivity >3 kPa−1) and high bending stability.

How to manage an arterial catheter.

Rationale and key points This article provides nurses with information on the safe and effective use and management of arterial catheters, the gold standard for accurate blood pressure measurement and routine serial blood gas sampling in critical care. Arterial catheters are used when real-time blood pressure monitoring is required, such as when there is a risk of significant blood loss. ▶Arterial catheters provide real-time blood pressure monitoring, enabling rapid identification of changes in blood pressure and guiding fluid resuscitation. ▶Arterial catheters can be used to take blood samples without having to perform multiple arterial or venous punctures. Reflective activity Clinical skills articles can help update your practice and ensure it remains evidence based. Apply this article to your practice. Reflect on and write a short account of: 1.How this article will change your practice when managing a patient with an arterial catheter. 2.Any further learning needs you have identified. Subscribers can upload their reflective accounts at: rcni.com/portfolio.

Wireless Batteryless Implantable Blood Pressure Monitoring Microsystem for Small Laboratory Animals

A novel, wireless, batteryless, implantable blood pressure monitoring microsystem for small laboratory animals is developed for advanced biological and system biology research. The system employs an instrumented elastic circular cuff, wrapped around a blood vessel, for real-time blood pressure monitoring. The elastic circular cuff is made of soft bio-compatible silicone material, which is filled with bio-compatible insulating fluid with an immersed microelectromechanical systems (MEMS) pressure sensor and integrated electronic system to detect a down-scaled vessel blood pressure waveform. This technique avoids vessel penetration and substantially minimizes vessel restriction due to the soft cuff elasticity, thus attractive for long-term monitoring. A large-model engineering experiment is first developed to verify and demonstrate the concept. A miniature prototype monitoring cuff is then fabricated and implanted in two laboratory rats to evaluate its functionality. A wireless and batteryless monitoring microsystem is then implanted and characterized in a laboratory rat. The measured <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> blood pressure waveform by the microsystem and a reference waveform recorded by a commercial catheter-tip transducer are closely matched in shape with a constant scaling factor, demonstrating a blood pressure signal with high fidelity can be wirelessly obtained by the implantable monitoring microsystem. The overall implant dissipates 300 ¿W, which is powered by an external adaptive RF powering source.

A Wireless and Batteryless 10-Bit Implantable Blood Pressure Sensing Microsystem With Adaptive RF Powering for Real-Time Laboratory Mice Monitoring

An implantable real-time blood pressure monitoring microsystem for laboratory mice has been demonstrated. The system achieves a 10-bit blood pressure sensing resolution and can wirelessly transmit the pressure information to an external unit. The implantable device is operated in a batteryless manner, powered by an external RF power source. The received RF power level can be sensed and wirelessly transmitted along with blood pressure signal for feedback control of the external RF power. The microsystem employs an instrumented silicone cuff, wrapped around a blood vessel with a diameter of approximately 200 ?m, for blood pressure monitoring. The cuff is filled by low-viscosity silicone oil with an immersed MEMS capacitive pressure sensor and integrated electronic system to detect a down-scaled vessel blood pressure waveform with a scaling factor of approximately 0.1. The integrated electronic system, consisting of a capacitance-to-voltage converter, an 11-bit ADC, an adaptive RF powering system, an oscillator-based 433 MHz FSK transmitter and digital control circuitry, is fabricated in a 1.5 ?m CMOS process and dissipates a power of 300 ?W. The packaged microsystem weighs 130 milligram and achieves a capacitive sensing resolution of 75 aF over 1 kHz bandwidth, equivalent to a pressure sensing resolution of 1 mmHg inside an animal vessel, with a dynamic range of 60 dB. Untethered laboratory animal in vivo evaluation demonstrates that the microsystem can capture real-time blood pressure information with a high fidelity under an adaptive RF powering and wireless data telemetry condition.

MRSA infected pseudoaneurysms of the radial artery

The use of radial artery catheters for real-time blood pressure monitoring and arterial blood gas sampling has become commonplace in both intensive care and high dependency units. Although this procedure is relatively safe, it can be complicated by local infection leading to pseudoaneurysm formation. In this report we describe three cases of pseudoaneurysm formation following prolonged radial catheter placement, with evidence of local methicillin resistant staphylococcus aureus (MRSA) infection. With the growing problem of in-hospital MRSA colonisation, the report aims to emphasize the need for vigilance for this complication and reinforce the importance of careful asepsis. In all cases the pseudoaneurysms were successfully treated with local ligation of the radial artery, without subsequent ischaemic complications. Allen's test was performed to ensure sufficient collateral circulation prior to surgery.

Real-time blood pressure monitoring in physiological experiments using an Apple II microcomputer

The paper describes a program used for real-time blood pressure monitoring. A simple method allowing interactive control of the decision criteria is used for upstroke detection. The blood pressure signal is characterized by means of 8 parameters, computed for every cycle. The program offers two graphic modes: plotting ( a) the original signal and ( b) the computed variables. Other useful programs are presented together with the BP/MONITOR to allow use of the Apple II as digital memory scope in different working modes.