Intermittent Measurements Research Articles

Deviating vital signs in continuous monitoring prior to discharge and risk of readmission: an observational study.

Premature discharge may result in readmission while longer hospitalization may increase risk of complications such as immobilization and reduce hospital capacity. Continuous monitoring detects more deviating vital signs than intermittent measurements and may help identify patients at risk of deterioration after discharge. We aimed to investigate the association between deviating vital signs detected by continuous monitoring prior to discharge and risk of readmission within 30days. Patients undergoing elective major abdominal surgery or admitted with acute exacerbation of chronic obstructive pulmonary disease were included in this study. Eligible patients had vital signs monitored continuously within the last 24h prior to discharge. The association between sustained deviated vital signs and readmission risk was analyzed by using Mann-Whitney's U test and Chi-square test. A total of 51 out of 265 patients (19%) were readmitted within 30days. Deviated respiratory vital signs occurred frequently in both groups: desaturation < 88% for at least ten minutes was seen in 66% of patients who were readmitted and in 62% of those who were not (p = 0.62) while desaturation < 85% for at least five minutes was seen in 58% of readmitted and 52% of non-readmitted patients (p = 0.5). At least one sustained deviated vital sign was detected in 90% and 85% of readmitted patients and non-readmitted patients, respectively (p = 0.2). Deviating vital signs prior to hospital discharge were frequent but not associated with increased risk of readmission within 30days. Further exploration of deviating vital signs using continuous monitoring is needed.

Quadratic filtering for non-Gaussian stochastic parameter systems with buffer-aided strategy

This paper is concerned with the quadratic filtering problem for a class of linear discrete time-varying systems with non-Gaussian stochastic parameters and intermittent measurements. In order to improve the filtering performance, a buffer-aided strategy is used to store the historical measurement data which is sent to the filter via a shared communication channel at each transmission instant. The main objective of this paper is to design a quadratic filter to estimate the states of the considered non-Gaussian stochastic systems by using the buffer-aided strategy. Specifically, an augmented system is constructed by combining the original system states and their second-order Kronecker powers. As such, the considered quadratic filtering problem amounts to the Kalman filtering problem for the augmented system. The filtering error covariance (FEC) conditioned on the transmission intervals is firstly derived recursively and then is minimized by choosing the suitable filtering gains. Moreover, sufficient conditions are deduced to guarantee the boundedness of both the FEC and the conditional FEC. Finally, two illustrative examples are provided to demonstrate the effectiveness of the proposed filtering method.

Design of intermittent continuous measurement of radon concentration in water

The U.S. Environmental Protection Agency established the maximum contaminant level limit for radon concentration in drinking water as 11.1 Bq L−1. A new device based on the bubbling method with a 290 mL sample bottle was designed for intermittent continuous measurement of water radon concentration. A STM32 is used to control the switch of the water pump and the valves. The Water-Radon-Measurement software written in C# is to connect RAD7 and calculate the water radon concentration automatically.

Estimating intermittency significance by means of surrogate data: implications for solar wind turbulence

Introduction: Intermittency is a property of turbulent astrophysical plasmas, such as the solar wind, that implies irregularity and fragmentation, leading to non-uniformity in the transfer rate of energy carried by nonlinear structures from large to small scales. We evaluated the intermittency level of the turbulent magnetic field measured by the Parker Solar Probe (PSP) in the slow solar wind in the proximity of the Sun during the probe’s first close encounter.Methods: A quantitative measure of intermittency could be deduced from the normalized fourth-order moment of the probability distribution functions, the flatness parameter. We calculated the flatness of the magnetic field data collected by the PSP between 1 and 9 November 2018. We observed that when dividing the data into contiguous time intervals of various lengths, ranging from 3 to 24 hours, the flatness computed for individual intervals differed significantly, suggesting a variation in intermittency from “quieter” to more intermittent intervals. In order to quantify this variability, we applied an elaborate statistical test tailored to identify nonlinear dynamics in a time series. Our approach is based on evaluating the flatness of a set of surrogate data built from the original PSP data in such a way that all nonlinear correlations contained in the dynamics of the signal are eliminated. Nevertheless, the surrogate data are otherwise consistent with the “underlying” linear process, i.e., the null hypothesis that we want to falsify. If a discriminating statistic for the original signal, such as the flatness parameter, is found to be significantly different from that of the ensemble of surrogates, then the null hypothesis is not valid, and we can conclude that the computed flatness reliably reflects the intermittency level of the underlying nonlinear processes.Results and discussion: We determined that the non-stationarity of the time series strongly influences the flatness of both the data and the surrogates and that the null hypothesis cannot be falsified. A global fit of the structure functions revealed a decrease in flatness at scales smaller than a few seconds: intermittency is reduced in this scale range. This behavior was mirrored by the spectral analysis, which was suggestive of an acceleration of the energy cascade at the high-frequency end of the inertial regime.

Non-Canonical Activin A Signaling Stimulates Context-Dependent and Cellular-Specific Outcomes in CRC to Promote Tumor Cell Migration and Immune Tolerance.

We have shown that activin A (activin), a TGF-β superfamily member, has pro-metastatic effects in colorectal cancer (CRC). In lung cancer, activin activates pro-metastatic pathways to enhance tumor cell survival and migration while augmenting CD4+ to CD8+ communications to promote cytotoxicity. Here, we hypothesized that activin exerts cell-specific effects in the tumor microenvironment (TME) of CRC to promote anti-tumoral activity of immune cells and the pro-metastatic behavior of tumor cells in a cell-specific and context-dependent manner. We generated an Smad4 epithelial cell specific knockout (Smad4-/-) which was crossed with TS4-Cre mice to identify SMAD-specific changes in CRC. We also performed IHC and digital spatial profiling (DSP) of tissue microarrays (TMAs) obtained from 1055 stage II and III CRC patients in the QUASAR 2 clinical trial. We transfected the CRC cells to reduce their activin production and injected them into mice with intermittent tumor measurements to determine how cancer-derived activin alters tumor growth in vivo. In vivo, Smad4-/- mice displayed elevated colonic activin and pAKT expression and increased mortality. IHC analysis of the TMA samples revealed increased activin was required for TGF-β-associated improved outcomes in CRC. DSP analysis identified that activin co-localization in the stroma was coupled with increases in T-cell exhaustion markers, activation markers of antigen presenting cells (APCs), and effectors of the PI3K/AKT pathway. Activin-stimulated PI3K-dependent CRC transwell migration, and the in vivo loss of activin lead to smaller CRC tumors. Taken together, activin is a targetable, highly context-dependent molecule with effects on CRC growth, migration, and TME immune plasticity.

Cost savings through continuous vital sign monitoring in the medical-surgical unit

ObjectiveThis study aimed to determine the potential cost-savings for implementing continuous vital sign monitoring in a hospital’s medical-surgical units.MethodsA cost-savings analysis was designed to calculate potential cost-savings for an average-sized U.S. community hospital (153 total beds) over a 1-year time horizon. Analysis parameters were extracted from national databases and previous studies that compared outcomes for patients receiving continuous vital sign monitoring (SpO2, HR, and RR) or standard of care (intermittent vital sign measurements) in medical-surgical units based on a targeted literature review. Clinical parameters and associated costs served as analysis inputs. The analysis outputs were costs and potential cost-savings using a 50% and 100% adoption rate of continuous monitoring technologies across the medical-surgical unit.ResultsPotential annual cost-savings for in-hospital medical-surgical stays were estimated at $3,414,709 (2022 USD) and $6,829,418 for a 50% and 100% adoption rate, respectively. The cost-savings for an adoption rate of 100% equated to a ∼14% reduction in the overall annual cost of medical-surgical unit stays for an average-sized hospital. The largest contribution to potential cost-savings came from patients that avoided serious adverse events that require transfer to the intensive care unit; this resulted in annual cost-savings from reduced average length of stay between $1,756,613 and $3,513,226 (50% and 100% adoption rate, respectively). Additional cost-savings can be attained from reductions in in-hospital cardiac arrest-associated hospitalizations and decreased rapid response team activation.ConclusionsOur findings demonstrate that there is the potential for cost-savings of over $6.8 million dollars per year in an average-sized US community hospital by improving patient outcomes through implementation of continuous monitoring technologies in medical-surgical units. Continuous vital sign monitoring technologies that increase patient mobility and facilitate recovery may further contribute to cost-savings and should be considered for economic analyses. Future research is needed to explore these health-related outcomes.

Process Evaluation of a Wireless Wearable Continuous Vital Signs Monitoring Intervention in 2 General Hospital Wards: Mixed Methods Study.

Continuous monitoring of vital signs (CMVS) using wearable wireless sensors is increasingly available to patients in general wards and can improve outcomes and reduce nurse workload. To assess the potential impact of such systems, successful implementation is important. We developed a CMVS intervention and implementation strategy and evaluated its success in 2 general wards. We aimed to assess and compare intervention fidelity in 2 wards (internal medicine and general surgery) of a large teaching hospital. A mixed methods sequential explanatory design was used. After thorough training and preparation, CMVS was implemented-in parallel with the standard intermittent manual measurements-and executed for 6 months in each ward. Heart rate and respiratory rate were measured using a chest-worn wearable sensor, and vital sign trends were visualized on a digital platform. Trends were routinely assessed and reported each nursing shift without automated alarms. The primary outcome was intervention fidelity, defined as the proportion of written reports and related nurse activities in case of deviating trends comparing early (months 1-2), mid- (months 3-4), and late (months 5-6) implementation periods. Explanatory interviews with nurses were conducted. The implementation strategy was executed as planned. A total of 358 patients were included, resulting in 45,113 monitored hours during 6142 nurse shifts. In total, 10.3% (37/358) of the sensors were replaced prematurely because of technical failure. Mean intervention fidelity was 70.7% (SD 20.4%) and higher in the surgical ward (73.6%, SD 18.1% vs 64.1%, SD 23.7%; P<.001). Fidelity decreased over the implementation period in the internal medicine ward (76%, 57%, and 48% at early, mid-, and late implementation, respectively; P<.001) but not significantly in the surgical ward (76% at early implementation vs 74% at midimplementation [P=.56] vs 70.7% at late implementation [P=.07]). No nursing activities were needed based on vital sign trends for 68.7% (246/358) of the patients. In 174 reports of 31.3% (112/358) of the patients, observed deviating trends led to 101 additional bedside assessments of patients and 73 consultations by physicians. The main themes that emerged during interviews (n=21) included the relative priority of CMVS in nurse work, the importance of nursing assessment, the relatively limited perceived benefits for patient care, and experienced mediocre usability of the technology. We successfully implemented a system for CMVS at scale in 2 hospital wards, but our results show that intervention fidelity decreased over time, more in the internal medicine ward than in the surgical ward. This decrease appeared to depend on multiple ward-specific factors. Nurses' perceptions regarding the value and benefits of the intervention varied. Implications for optimal implementation of CMVS include engaging nurses early, seamless integration into electronic health records, and sophisticated decision support tools for vital sign trend interpretation.

A Different Perspective on Air Pollution Measurements

This study aims to determine the air pollution in Karabük province. For this purpose, a new equipment has been designed. The equipment can measure the SO2, CO2, CO, CH4, NOX, O3, PM2.5, and VOC pollution alongside with many atmospheric parameters. The measurement period has been decided to be one year starting from June 2021. The measurement period was one year, starting from June 2021. The measurements were taken at fifty points with 8 portable intermittent equipment. Then hourly and monthly averages were calculated. The calculation of the averages depends on many statistical analyses. The mean (geometric, harmonic, root, interquartile, Winsorized), median, midrange, Skewness, and Kurtosis analyses were done to obtain correct daily, and monthly averages. These analyses are necessary to comment on the intermittent measurement averages. The analyses of the collected data showed that the concentrations are changing considerably through the measurement period. The highest concentration was observed for the SO2, CO, NOX, and PM2.5 with respective values of 186.4, 170, 204.9, and 265 µg/m3. All these values are dangerous for human health. Elevation, temperatures, atmospheric pressure, and wind are sensitive parameters for atmospheric pollution. In Karabük province, most of the measurement points are affected by multi-pollution sources. The scatter diagrams also support this fact. During winter months, the pollution increases instantly. However, O3 and VOC parameters show different trends as compared to other pollutants. The concentration of these two parameters, namely O3 and VOC, increases during spring months. The O3 and VOC increase by 78.1%, and 43.2%, respectively due to photochemical reactions in the atmosphere in spring.

Cuff-Less Blood Pressure Prediction Based on Photoplethysmography and Modified ResNet.

Cardiovascular disease (CVD) has become a common health problem of mankind, and the prevalence and mortality of CVD are rising on a year-to-year basis. Blood pressure (BP) is an important physiological parameter of the human body and also an important physiological indicator for the prevention and treatment of CVD. Existing intermittent measurement methods do not fully indicate the real BP status of the human body and cannot get rid of the restraining feeling of a cuff. Accordingly, this study proposed a deep learning network based on the ResNet34 framework for continuous prediction of BP using only the promising PPG signal. The high-quality PPG signals were first passed through a multi-scale feature extraction module after a series of pre-processing to expand the perceptive field and enhance the perception ability on features. Subsequently, useful feature information was then extracted by stacking multiple residual modules with channel attention to increase the accuracy of the model. Lastly, in the training stage, the Huber loss function was adopted to stabilize the iterative process and obtain the optimal solution of the model. On a subset of the MIMIC dataset, the errors of both SBP and DBP predicted by the model met the AAMI standards, while the accuracy of DBP reached Grade A of the BHS standard, and the accuracy of SBP almost reached Grade A of the BHS standard. The proposed method verifies the potential and feasibility of PPG signals combined with deep neural networks in the field of continuous BP monitoring. Furthermore, the method is easy to deploy in portable devices, and it is more consistent with the future trend of wearable blood-pressure-monitoring devices (e.g., smartphones and smartwatches).

Continuous monitoring is superior to manual measurements in detecting vital sign deviations in patients with COVID-19.

Patients admitted to the emergency care setting with COVID-19-infection can suffer from sudden clinical deterioration, but the extent of deviating vital signs in this group is still unclear. Wireless technology monitors patient vital signs continuously and might detect deviations earlier than intermittent measurements. The aim of this study was to determine frequency and duration of vital sign deviations using continuous monitoring compared to manual measurements. A secondary analysis was to compare deviations in patients admitted to ICU or having fatal outcome vs. those that were not. Two wireless sensors continuously monitored (CM) respiratory rate (RR), heart rate (HR), and peripheral arterial oxygen saturation (SpO2 ). Frequency and duration of vital sign deviations were compared with point measurements performed by clinical staff according to regional guidelines, the National Early Warning Score (NEWS). SpO2 < 92% for more than 60 min was detected in 92% of the patients with CM vs. 40% with NEWS (p < .00001). RR > 24 breaths per minute for more than 5 min were detected in 70% with CM vs. 33% using NEWS (p=.0001). HR ≥ 111 for more than 60 min was seen in 51% with CM and 22% with NEWS (p=.0002). Patients admitted to ICU or having fatal outcome had longer durations of RR > 24 brpm (p=.01), RR > 21 brpm (p=.01), SpO2 < 80% (p=.01), and SpO2 < 85% (p=.02) compared to patients that were not. Episodes of desaturation and tachypnea in hospitalized patients with COVID-19 infection are common and often not detected by routine measurements.

Adaptive Event-Triggered Interval Type-2 T-S Fuzzy Control for Lateral Dynamic Stabilization of AEVs With Intermittent Measurements and Actuator Failure

This article presents an adaptive event-triggered dynamic output feedback interval type-2 (IT-2) T-S fuzzy control method for autonomous electric vehicle systems. First, the IT-2 T-S fuzzy model is introduced to describe the nonlinear lateral dynamics of the vehicle systems. Second, a novel adaptive event-triggered strategy is designed to reduce the computational burden. Third, the phenomenon of intermittent measurements is depicted by the Bernoulli random distributed process, and the failure of the actuator is also included. According to the Lyapunov stability theory, an IT-2 T-S fuzzy dynamic output feedback controller (DOFC) is presented to ensure the random stability and performance of the vehicle systems. Finally, the effectiveness and real-time performance of the proposed control strategy are verified via numerical simulation and a hardware-in-the-loop (HIL) test platform.

Electrophysical processes in an electroterminator (with an intelligent system) with sliding contacts in the power circuit

This article presents data on the properties of sliding contacts during the rotation of the axis of a device for pre-sowing treatment of crop seeds, considers the issues of automation of intermittent power supply and measurement of electrical conductivity and temperature parameters of seed material in the process of electrotechnology. At the same time, the contact resistance of the power circuit, normalized moistening of sowing seeds, depending on the type of plants, was taken as the basis of the physical model. Smart system takes into account soil parameters (type, density, moisture content). In the initial period of seed treatment, moisture penetrates into the seed from the outside. therefore, the time of humidification and electrical treatment are the main factors. Depending on the seed variety, it will be possible to change the operating parameters of the electrical treatment of crop seeds. The work also carried out a review of the literature and mathematical calculations.

Scenario Adaptive Cuffless Blood Pressure Estimation by Integrating Cardiovascular Coupling Effects.

Adding cuffless blood pressure (BP) measurement function to wearable devices is of great value in the fight against hypertension. The widely used arterial pulse transit time (PTT)-based method for BP monitoring relies primarily on vascular status-determined BP models and typically exhibits degraded performance over time and is sensitive to measurement procedures. Developing alternative methods with improved accuracy and adaptability to various application scenarios is highly desired for cuffless BP measurement. In this work, we proposed a pattern-fusion (PF) method that incorporates cardiovascular coupling effects in the vascular model by combining three calculation modules - cardiac parameter extraction module, cardiac parameter-to-BP mapping module, and BP regulation module. Specifically, the first module combines feedforward, feedback, and propagation modes to model different modulation functions of a cardiovascular system and is responsible for extracting BP-related features from electrocardiography (ECG) and photoplethysmography (PPG) signals; the cardiac parameter-to-BP mapping module is used to map cardiac parameters into mean blood pressure (MBP) by fusing different features; finally, the BP regulation module recovers accurate systolic BP (SBP) and diastolic BP (DBP) from given MBP. With the concerted use of these three modules, the pattern fusion method consistently demonstrates excellent BP prediction accuracy in a variety of measurement scenarios and durations, exhibiting SBP/DBP mean absolute error (MAE) of 3.65/4.56 mmHg for the short-term (<10 mins) continuous measurement dataset, SBP/DBP MAE of 6.84/3.81 mmHg for the medium-term (avg. > 20 hours) continuous measurement dataset, and SBP/DBP MAE of 6.24/3.65 mmHg for the long-term (> 1 month) intermittent measurement dataset.

An Integrated Nonlinear Analysis (INA) Software for Space Plasma Turbulence

AbstractWe built an integrated nonlinear analysis software (INA)‐designed to study space plasma turbulence and intermittency. The MATLAB programming environment was used for the algorithmic development and implementation of methods for spectral analysis, multiscale fluctuations and multifractal analysis. The performance of INA is demonstrated using magnetic field measurements during an inbound pass through the Earth's magnetosheath region of the Cluster 3 spacecraft. We show how specific features of the power spectral density can be mapped to localized time‐frequency regions in the spectrogram representation, and identify multiple intermittent events using the wavelet‐based local intermittency measure. Multiscale probability density functions showed clear departures from Gaussianity, signifying the presence of intermittency. Structure functions and rank‐ordered multifractal analysis revealed the multifractal nature of the analyzed signal. INA is freely distributed as a standalone executable file to any interested user, and provides an integrated, interactive, and user‐friendly environment in which one can import a data set, customize key analysis parameters, apply multiple methods on the same signal and then export high‐quality, publication‐ready figures. These are only a few of the many distinguishing features of INA.

In Vivo Monitoring of Acute and Intermittent Fatigue in Sport Climbing Using Near-Infrared Spectroscopy Wearable Biosensors

The objectification of acute fatigue (during isometric muscle contraction) and cumulative fatigue (due to multiple intermittent isometric muscle contractions) plays an important role in sport climbing. The data of 42 participants were used in the study. Climbing performance was operationalized using maximal climbing-specific holding time (CSHT) by performing dead hangs. The test started with an initial measurement of handgrip strength (HGS) followed by three intermittent measurements of CSHT and HGS. During the test, finger flexor muscle oxygen saturation (SmO2) was measured using a near-infrared spectroscopy wearable biosensor. Significant reductions in CSHT and HGS could be found (p < 0.001), which indicates that the consecutive maximal isometric holding introduces cumulative fatigue. The reduction in CSHT did not correlate with a reduction in HGS over multiple consecutive maximal dead hangs (p > 0.35). Furthermore, there were no significant differences in initial SmO2 level, SmO2 level at termination, SmO2 recovery, and mean negative slope of the SmO2 saturation reduction between the different measurements (p > 0.24). Significant differences were found between pre-, termination-, and recovery- (10 s after termination) SmO2 levels (p < 0.001). Therefore, monitoring acute fatigue using athletes' termination SmO2 saturation seems promising. By contrast, the measurement of HGS and muscle oxygen metabolism seems inappropriate for monitoring cumulative fatigue during intermittent isometric climbing-specific muscle contractions.

Unsteadiness characterisation of shock wave/turbulent boundary-layer interaction at moderate Reynolds number

A direct numerical simulation of an oblique shock wave impinging on a turbulent boundary layer at Mach number 2.28 is carried out at moderate Reynolds number, simulating flow conditions similar to those of the experiment by Dupont et al. (J. Fluid Mech., vol. 559, 2006, pp. 255–277). The low-frequency shock unsteadiness, whose characteristics have been the focus of considerable research efforts, is here investigated via the Morlet wavelet transform. Owing to its compact support in both physical and Fourier spaces, the wavelet transformation makes it possible to track the time evolution of the various scales of the wall-pressure fluctuations. This property also makes it possible to define a local intermittency measure, representing a frequency-dependent flatness factor, to pinpoint the bursts of energy that characterise the shock intermittency scale by scale. As a major result, wavelet decomposition shows that the broadband shock movement is actually the result of a collection of sparse events in time, each characterised by its own temporal scale. This feature is hidden by the classical Fourier analysis, which can only show the time-averaged behaviour. Then, we propose a procedure to process any relevant time series, such as the time history of the wall pressure or that of the separation bubble extent, in which we use a condition based on the local intermittency measure to filter out the turbulent content in the proximity of the shock foot and to isolate only the intermittent component of the signal. In addition, wavelet analysis reveals the intermittent behaviour also of the breathing motion of the recirculation bubble behind the reflected shock, and allows us to detect a direct, partial correspondence between the most significant intermittent events of the separation region and those of the wall pressure at the foot of the shock.

Tracking Control of Quadrotor with Intermittent Target Measurements: A Stochastic Switched Systems Approach

This paper is devoted to the investigation of target tracking control of quadrotor with intermittent measurements, i.e., the measurements of target position are not continuously available. A stochastic switched systems approach is utilized to formulate such a tracking process of quadrotor by splitting it into two modes according to whether the measurements are available. The mode switching of the underlying system is subject to a Markov process to account for the inherent non-memory randomness of the dwell time of each mode, in contrast with the existing studies that impractically require the duration of the measurements to be greater than a given constant. The stability criteria for the underlying system are derived, upon which a switched controller is designed for the quadrotor position control, rather than the determination of the bounds of the dwell time for given pre-designed controllers in each mode. Simulations are presented to demonstrate the effectiveness of the developed theoretical results and the superiority of the designed switched controller for tracking control of quadrotor with intermittent target measurements.

Study on ventilation issues in urban nursery facilities: Long-term field survey in Yokohama, Japan

In many urban nursery facilities in Japan, daily ventilation behavior is restricted, and poor indoor air quality has been an issue of concern. However, the lack of specific common standards for indoor environments, including ventilation in nursery facilities, has left the issue unresolved in Japan. The purpose of this study is to clarify ventilation issues at nursery facilities in urban areas and indicate future measures. To this end, indoor air quality was analyzed using data from intermittent measurements taken between 2014 and 2022 at 21 nursery facilities in Yokohama City. As a result, the nursery facilities were classified into three categories based on nursery teachers’ ventilation behavior: “window-ventilation type,” “mechanical-ventilation type,” and “combined-ventilation type.” There was a significant difference (p-value &lt;0.001) in the mean CO2 concentration between the window-ventilation type and the mechanical-ventilation type, and between the window-ventilation type and the combined-ventilation type, confirming the difference indoor air quality due to the difference in ventilation behavior. It was clear that the mechanical-ventilation type and combined-ventilation type had significantly lower compliance rates with the minimum ventilation rate required by the Japanese Building Standard Law (20 m3/h), which buildings must have at a minimum.

S-58-3: HOW COULD CONTINUOUS CUFFLESS AUTOMATED BLOOD PRESSURE MEASUREMENT DEVICES CONTRIBUTE TO HYPERTENSION MANAGEMENT?

Evidence that hypertension is the most importat global risk factor for cardiovascular morbidity and mortality, and demonstration of the cardiovascular protection offered by antihypertensive treatment, have been based on upper-arm cuff blood pressure (BP) measurements. This approach is recommended by current hypertension guidelines for BP measurement in clinical practice, as well as for validation of novel BP measuring devices. However, the spot or intermittent BP measurements in static conditions allowed by arm-cuff devices are unable to identify and track the continuous and rapid BP changes characterizing daily life. Moreover, cuff-based BP measurements are exposed to errors related to cuff size, shape and positioning, and cuff inflation may itself induce an alerting response and produce discomfort in the users during daily activities and in particular during sleep, which may modify the measured BP levels. To face these issues, use of continuous recordings techniques, not based on arm-cuff inflation, would be required. This is possible through intra-arterial recordings, which however are not feasible in daily practice because of their invasiveness. An alternative solution is represented by photoplethysmographic volume-clamp method for finger BP monitoring which, however, is difficult to implement in clinical practice because of its cost and complexity. Technological progress is now offering an increasingly large and heterogeneous series of cuffless BP monitors, which estimate BP based on sensors, signal processing and algorithms embedded in wearable devices, smartphones or pocket devices. These cuffless devices might allow for comfortable and continuous BP recordings, detecting rapid BP changes during day and night sleep, thus offering information on both short, mid and long term BP variability. Cuffless devices might also be useful for continuous non invasive BP monitoring in different clinical settings, including ICUs, during anaesthesia, in patients with arrhythmias, hypotension/syncope, and other transient conditions affecting BP levels and variability. Moreover, cuffless BP measurement devices connected to telemonitoring facilities or smartphones apps may improve patients empowerment, adherence to treatment and long-term BP control. In spite of all these potential advantages, however, cuffless BP devices have to face specific accuracy issues, which would need refinement of specific validation protocols aimed at testing the need of individual calibration, the stability of measurements after calibration and the device actual ability to track BP changes before they might be recommended for clinical use.

Target Tracking Subject to Intermittent Measurements Using Attention Deep Neural Networks

This letter presents a novel estimator and predictor framework for target tracking applications that estimates the pose of a mobile target that intermittently leaves the field-of-view (FOV) of a mobile agent’s camera. Specifically, the framework uses an attention deep motion model network (DMMN) to estimate the dynamics of the target when the target is in the agent’s FOV and uses the DMMN to predict the position, orientation, and velocity of the target when the target is outside the agent’s FOV. A Lyapunov-based stability analysis is performed to determine the maximum dwell-time condition on target measurement availability, and experimental results are provided to demonstrate the performance of the proposed framework.