Reference Monitor Research Articles

Occupational safety and health hazards in artisanal gold mines in western and Nyanza region, Kenya

Artisanal and small-scale gold mining (ASSGM) has experienced rapid growth due to mineral value and increasing poverty level in western and Nyanza regions in Kenya. The sub-sector has hazardous tasks occasioned by chemical exposures to such substances as mercury, physical strain and repetitive movements associated with extractive tasks challenge which vary from region to region and site to site. This paper reports findings of a study conducted on ASSGM in Kakamega (Roster mine and Ikolomani) and Migori (Masara-Suna West and Francis - Suna East) counties to assess workplace safety, health risk and good health practice among a population of one thousand four hundred (1400) miners and non-miners to identify and determine levels of health hazard in the sector. Descriptive cross-sectional design that involved stratified sampling technique with three broad stages was used: dividing mining and non-mining population in sub-groups (miners, foremen/supervisors, and head of households) at sites in administering to them research instrument using a simple random technique. Levels of airborne particulate matter (PM2.5 and PM10) were determined both at mining sites and away from mining sites using low cost monitor sensor (PA-11-SD Purple air sensor). The low-cost monitor sensor data was corrected using collocational data obtained using a continuous particulate monitor (BAM 1020) reference monitor in a similar location. SPSS version 25.0 was used to analyse qualitative data. The study found that common sources of hazards included handling elemental mercury with bare hands during amalgamation and exposure to fumes during refining raw sponge-like gold. Aaverage 24-hour variation cycle for (PM2.5 and PM10) was 117.11±14.47 and 195.18±15.35 μg/m3 in ambient air respectively at all mining sites. Histograms were used to present frequency distribution of variations for (PM2.5 and PM10) from mining activity. The average humidity and temperature variations of artisanal gold mining were in the range of (45-35) percentage (% RH) and (26-28)0C respectively. The study concluded that there were high risk cycle exposures to airborne particulate matter contaminants at artisanal gold mining sites as compared to non- mining sites. The study recommends that the county government should give priority to developing safe guidelines to ASSGM. The central government should also come up with guidelines on Occupational Safety and Health in artisanal gold mining to facilitate compliance with OSH requirements in the sector and offer effective participative training.

Wearable ring bioelectrical impedance analyzer for estimation and monitoring of body fat

The World Health Organization has declared obesity as one of the fastest growing global epidemics. People suffering from obesity are at an increased risk of serious health conditions including stroke, diabetes, high blood pressure, and other chronic diseases caused by excess fat in the body. To study and control this obesity epidemic, precise measurement of the body fat mass is necessary. Bioelectrical impedance analysis (BIA) is a common yet effective method for body composition, especially fat mass, measurement in which the electrical impedance of a human body is measured. Here we report a novel wireless BIA device, in the form of a wearable ring, for estimating the body fat as well as a smartphone application for users to manage and track their health data. The wearable analyzer was compared with an off-the-shelf body fat monitor in terms of performance for 40 healthy volunteers. In addition, the small, dry electrodes used in the ring analyzer are compared with traditional gel-based electrodes. Although the dry electrodes impose a larger skin-electrode contact impedance (5.18 ± 0.655 kΩ) than gel-based electrodes (933.37 ± 40.06 Ω), the designed system provides critical compensation for the higher electrode impedance and the parasitic effects for the dry electrodes. With the compensation implemented, these two types of electrodes are highly correlated with correlation coefficients r = 0.96 for resistance and r = 0.93 for reactance. Body fat estimation equations proposed by four different groups are analyzed and compared using the results from the wearable ring device. Our ring analyzer and the reference monitor demonstrate a linear regression with a strong correlation (r = 0.90) for estimating fat mass. Furthermore, the Bland-Altman plot shows that only 2 out of 40 subjects lie outside the 95% limit of agreement. All these findings show that the ring BIA system is highly portable, easy to use, and with comparable performance to large reference analyzers.

Development of enhance reference monitor algorithm for software defined networking (SDN) controller for 5G security

The aim of this research is to develop an enhanced reference monitor algorithm for Software Defined Networking (SDN) controller for 5G security. It is anticipated that by 2025, the network infrastructure should be able to provide connectivity for almost everything. This is expected to bring over 50 billion connections which cannot be handled by the current 4G. While 4G networks main focus is ubiquitous mobile broadband, 5G technology characteristics will have to increase immensely. The flexibility provided by software is key to meeting the unforeseen future service requirement. In this regard, Software Defined Networking (SDN) has recently gathered momentum in the networking industry and specific standard is yet to be adopted on how to check security challenges on SDN for 5G. This work proposes to adopt 5-ENSURE framework of integrating Reference Monitor (RM) to SDN controllers in order to impose access control policy. The Study will also isolate and handle malicious packets in a distributed manner among nodes rather than only permitting or denying access based on access policy. This work would contribute in security standardization of SDN for 5G which is currently under study across the world.

Few-Shot Calibration of Low-Cost Air Pollution (PM$_{2.5}$) Sensors Using Meta Learning

Low-cost particulate matter sensors are transforming air quality monitoring because they have greater mobility as compared to reference monitors. Calibration of these low-cost sensors requires training data from codeployed reference monitors. Machine learning-based calibration gives better performance than conventional techniques, but requires a large amount of training data from the sensor, to be calibrated, codeployed with a reference monitor. In this letter, we propose novel transfer learning methods for quick calibration of sensors with minimal co-deployment with reference monitors. Transfer learning utilizes a large amount of data from other sensors along with a limited amount of data from the target sensor. Our experimentation finds the proposed model-agnostic-meta learning-based transfer learning method to be significantly more effective over other competitive baselines, reducing the calibration errors by 32% and 15% relative to the raw observations and the best baseline, respectively.

High Assurance in the Twenty-First Century With Roger Schell

Bob Blakley: Welcome, everybody, to episode three of the IEEE Over the Rainbow podcast. I am your host Bob Blakley, and we’re here today with one of the founders of the field of information security, Roger Schell. Roger, back in the early 1980s, was one of the leaders of the production of a U.S. government standard called the Orange Book [formally titled the Trusted Computer System Evaluation Criteria, (TCSEC)], which essentially defined the model for a secure computer system. I have a copy of it here. Roger, you’ll be happy to see that I used it heavily enough that I had to take the staples out. I think it’s probably a good time to be having this conversation because this year is the 50th anniversary of the reference monitor model. Nineteen seventy-two saw the publication of the Anderson report, which introduced the concept, as far as I’m aware, in the public literature—and that’ll be 50 years ago this year. And—as I think you’re aware, Roger—the title of our podcast is a sort of multilayered pun, and one of the aspects of the pun is a reference to the Rainbow Series, which the Orange Book was the inaugural volume of. One of the sly suggestions we were hinting at in the title was that, in some sense, the computer security industry is over the Rainbow Series—over in the sense of sort of wanting to leave it in the past. But I think one of the things that we’re going to talk about today is that it’s not easy to leave the Orange Book in the past and also possibly not wise. So, with that introduction, Lorrie, I’ll hand it to you to start our questions.

Sampling Low Air Pollution Concentrations at a Neighborhood Scale in a Desert U.S. Metropolis with Volatile Weather Patterns.

Background: Neighborhood-scale air pollution sampling methods have been used in a range of settings but not in low air pollution airsheds with extreme weather events such as volatile precipitation patterns and extreme summer heat and aridity—all of which will become increasingly common with climate change. The desert U.S. metropolis of Tucson, AZ, has historically low air pollution and a climate marked by volatile weather, presenting a unique opportunity. Methods: We adapted neighborhood-scale air pollution sampling methods to measure ambient NO2, NOx, and PM2.5 and PM10 in Tucson, AZ. Results: The air pollution concentrations in this location were well below regulatory guidelines and those of other locations using the same methods. While NO2 and NOx were reliably measured, PM2.5 measurements were moderately correlated with those from a collocated reference monitor (r = 0.41, p = 0.13), potentially because of a combination of differences in inlet heights, oversampling of acutely high PM2.5 events, and/or pump operation beyond temperature specifications. Conclusion: As the climate changes, sampling methods should be reevaluated for accuracy and precision, especially those that do not operate continuously. This is even more critical for low-pollution airsheds, as studies on low air pollution concentrations will help determine how such ambient exposures relate to health outcomes.

Energy-Efficient Monitoring of Fine Particulate Matter with Tiny Aerosol Conditioner.

Fine particulate matter (PM) is associated with an increased risk of respiratory and cardiovascular diseases. Fine PM absorbs water molecules at high relative humidity, and then their size grows. Such hygroscopic growth causes a large error when monitoring PM concentrations. To lower the relative humidity, monitors use an indirect heating device, which is large and consumes large amounts of power. The problem with conventional particle separators is that their efficiency depends on temperature and humidity, and their traditional structure, which lets air flow downward. As such, this paper addresses these problems and presents a PM monitor with a new type of dryer that is free from these problems. The proposed monitor requires less energy and has an efficient dehumidifier and a new structure in which air flows upward. The presented experiments were conducted to compare the proposed device with a reference monitor managed by a governmental institute, and to evaluate the effect of the dehumidifier, the relative precision of the proposed devices, and the correlation with the reference monitor. The experimental results showed that the proposed monitor satisfies the U.S. EPA indicators for class III monitors.

АНАЛИЗ БЕЗОПАСНОСТИ ПОДСИСТЕМ ЛОКАЛЬНОЙ АУТЕНТИФИКАЦИИ ОС СЕМЕЙСТВ WINDOWS И LINUX

The paper is devoted to the security analysis of authority subsystem services for Windows and Linux operating systems. The paper provides security analysis for both local and network-based authentication in Windows. The Mimikatz (France) will be presented to demonstrate attacks on the authentication subsystem. Mimikatz is a software tool that can extract users’ credentials and password information from the memory of the LSASS process. To prevent such attacks on process memory Windows OS includes several security mechanisms: Security Reference Monitor, Protected Process Light, and Virtualization-Based Security. However, attackers can bypass these mechanisms to get illegal access to the process memory and steal users’ credentials. A similar analysis of the local authority subsystem for Linux OSes shows that gnome-keyring-daemon stores the users’ passwords in plain text. As a result, attackers can easily extract this sensitive information using memory forensics techniques via user-mode applications. Several modern Linux Distributions based on Red Hat Enterprise Linux (RHEL) still have this security issue: CentOS, Ubuntu, GNU/ Linux Rolling. Experts have developed software tools to locate and remove passwords from the memory to tackle this security challenge: MimiPenguin (USA) and Mimipy (USA). Comparison analysis of these tools reveals their drawbacks: these security tools cannot locate passwords with Unicode characters, and these tools have low speed. The proposed security solution called MimiDove is designed to solve both these issues. MimiDove expands features of MimiPenguin and Mimipy by locating and deleting passwords with ASCII and Unicode characters. MimiDove is faster than MimiPenguin and Mimipy.

Continuous vital sign monitoring using a wearable patch sensor in obese patients: a validation study in a clinical setting.

Our aim was to determine the agreement of heart rate (HR) and respiratory rate (RR) measurements by the Philips Biosensor with a reference monitor (General Electric Carescape B650) in severely obese patients during and after bariatric surgery. Additionally, sensor reliability was assessed. Ninety-four severely obese patients were monitored with both the Biosensor and reference monitor during and after bariatric surgery. Agreement was defined as the mean absolute difference between both monitoring devices. Bland Altman plots and Clarke Error Grid analysis (CEG) were used to visualise differences. Sensor reliability was reflected by the amount, duration and causes of data loss. The mean absolute difference for HR was 1.26 beats per minute (bpm) (SD 0.84) during surgery and 1.84bpm (SD 1.22) during recovery, and never exceeded the 8bpm limit of agreement. The mean absolute difference for RR was 1.78 breaths per minute (brpm) (SD 1.90) during surgery and 4.24 brpm (SD 2.75) during recovery. The Biosensor's RR measurements exceeded the 2 brpm limit of agreement in 58% of the compared measurements. Averaging 15min of measurements for both devices improved agreement. CEG showed that 99% of averaged RR measurements resulted in adequate treatment. Data loss was limited to 4.5% of the total duration of measurements for RR. No clear causes for data loss were found. The Biosensor is suitable for remote monitoring of HR, but not RR in morbidly obese patients. Future research should focus on improving RR measurements, the interpretation of continuous data, and development of smart alarm systems.

Accuracy of vital parameters measured by a wearable patch following major abdominal cancer surgery

IntroductionRecent advances in wearable technology allow for the development of wirelessly connected sensors to continuously measure vital parameters in the general ward or even at home. The present study assesses the accuracy of a wearable patch (Healthdot) for continuous monitoring of heartrate (HR) and respiration rate (RR). Materials and methodsThe Healthdot measures HR and RR by means of chest accelerometry. The study population consisted of patients following major abdominal oncological surgery. The analysis focused on the agreement between HR and RR measured by the Healthdot and the gold standard patient monitor in the intensive and post-anesthesia care unit. ResultsFor HR, a total of 112 h of measurements was collected in 26 patients. For RR, a total of 102 h of measurements was collected in 21 patients. On second to second analysis, 97% of the HR and 87% of the RR measurements were within 5 bpm and 3 rpm of the reference monitor. Assessment of 5-min averaged data resulted in 96% of the HR and 95% of the RR measurements within 5 bpm and 3 rpm of the reference monitor. A Clarke error grid analysis showed that 100% of the HR and 99.4% of the 5-min averaged data was clinically acceptable. ConclusionThe Healthdot accurately measured HR and RR in a cohort of patients recovering from major abdominal surgery, provided that good quality data was obtained. These results push the Healthdot forward as a clinically acceptable tool in low acuity settings for unobtrusive, automatic, wireless and continuous monitoring.

Stability of DNA methylation and chromatin accessibility in structurally diverse maize genomes.

Accessible chromatin and unmethylated DNA are associated with many genes and cis-regulatory elements. Attempts to understand natural variation for accessible chromatin regions (ACRs) and unmethylated regions (UMRs) often rely upon alignments to a single reference genome. This limits the ability to assess regions that are absent in the reference genome assembly and monitor how nearby structural variants influence variation in chromatin state. In this study, de novo genome assemblies for four maize inbreds (B73, Mo17, Oh43, and W22) are utilized to assess chromatin accessibility and DNA methylation patterns in a pan-genome context. A more complete set of UMRs and ACRs can be identified when chromatin data are aligned to the matched genome rather than a single reference genome. While there are UMRs and ACRs present within genomic regions that are not shared between genotypes, these features are 6- to 12-fold enriched within regions between genomes. Characterization of UMRs present within shared genomic regions reveals that most UMRs maintain the unmethylated state in other genotypes with only ∼5% being polymorphic between genotypes. However, the majority (71%) of UMRs that are shared between genotypes only exhibit partial overlaps suggesting that the boundaries between methylated and unmethylated DNA are dynamic. This instability is not solely due to sequence variation as these partially overlapping UMRs are frequently found within genomic regions that lack sequence variation. The ability to compare chromatin properties among individuals with structural variation enables pan-epigenome analyses to study the sources of variation for accessible chromatin and unmethylated DNA.

Barometric coefficient dependence on the geomagnetic cutoff rigidity of neutron monitors

Several studies have been showing that cosmic ray intensity variations observed at the Earth surface can be a useful tool to analyze and predict space weather and climate phenomena. However, before reach the ground level, the cosmic ray particles interact with different atmospheric atoms. This results in the generation of different secondary particles that are differently affected by atmospheric effects. For example, data from neutron monitors, which are widely used to study cosmic ray flux changes related to space phenomena, are significantly affected by atmospheric pressure changes. Thus, for a more detailed study of these instruments’ data, it is necessary to know very well how works the pressure affects secondary neutrons. In this way, we seek to understand how this effect changes according to the cosmic rays’ energy. Thus, in this work, we compare how the barometric coefficient ( β ), which quantifies the pressure effect on the cosmic ray intensity, changes with the geomagnetic cutoff rigidity ( R C ), which quantifies the minimal rigidity/energy that a primary particle needs to reach a given location in a chosen direction. To do that, we used data recorded between January 2008 to December 2016 by several neutron monitors around the globe with R C from 0.1 to 8.3 GV. We experimentally obtained β in two ways: (I) the typical one, which does not explicitly consider isotropic variations unrelated to the pressure effect; and (II) one that considers such variations by using coupling coefficients and a reference neutron monitor station. Like other works, we found that the pressure effect seems to present a logarithmic relation with the cutoff rigidity when we estimate β through the typical method used. On the other hand, we found that the pressure effect linearly decreases with the cutoff rigidity when considering an adjustment in this typical method to eliminate external isotropic variations. This linear relation appears to not change accordingly to the reference monitor chosen. These results enhance our knowledge of how the pressure effect globally acts on the cosmic ray intensity observed at ground level and, consequently, improves future analysis about global changes in the cosmic ray flux related to space weather phenomena.

Improved PM2.5 concentration estimates from low-cost sensors using calibration models categorized by relative humidity

Low-Cost Sensors (LCS) of fine particulate matter (PM2.5) have been widely used to supplement regular air quality monitoring stations. However, the sensor output is impacted by environmental factors, especially relative humidity, and must be calibrated to yield estimates of concentrations. In this study, we evaluate the performance of a linear model and a generalized additive model (GAM) to calibrate the output of LCS PM2.5 measurements in terms of different relative humidity levels. The method is based on co-located measurements from an LCS and a conventional reference monitor at two sites in an urban area in northern China. A stepwise variable selection of air pollutant concentrations and meteorological observations is used to select inputs to the model in order to improve the calibration ability. The results show that when relative humidity is below 75%, linear calibration of LCS PM2.5 observations can output PM2.5 mass concentrations close to the reference method with a correlation coefficient (R2) of 0.86. When relative humidity is above 75%, the GAM calibration model significantly outperforms the linear model, with an R2 of approximately 0.83. Overall, the linear model exhibits good fitness in dry conditions, while the GAM captures PM2.5 variations best in humid conditions. We conclude that low-cost PM2.5 sensors are sensitive to relative humidity and that therefore condition-specific calibration methods need to be used to improve the quality of the data as well as to improve the match with reference measurements.Copyright © 2021 American Association for Aerosol Research

Neutron radiative capture cross section for sodium with covariance analysis

The neutron radiative capture cross sections measurement has been carried out for the $$^{23}$$ Na nucleus in the neutron energy region from 0.6 to 3.2 MeV using the neutron activation technique followed by off-line $$\gamma $$ -ray spectrometry. The measurement was made relative to the $$^{115}$$ In(n,n $$\prime $$ $$\gamma $$ ) $$^{115}\hbox {In}^{m}$$ reference monitor reaction cross section. The neutrons were produced via the $$^{7}$$ Li(p,n) $$^{7}$$ Be reaction. Detailed uncertainty propagation has been performed using the covariance analysis, and the measured cross sections are being reported with their uncertainties, covariance, and correlation matrix. The necessary corrections have been made for the low background neutron energy contribution, $$\gamma $$ -ray true coincidence summing, and self-attenuation process. The obtained neutron spectrum averaged cross sections of $$^{23}$$ Na(n, $$\gamma $$ ) $$^{24}$$ Na are discussed and compared with the existing cross sections data retrieved from the EXFOR database. EMPIRE-3.2 and TALYS-1.9 calculations were performed in order to determine the radiative capture cross section in this energy region. The present results are also compared with the evaluated nuclear data from ENDF/B-VIII.0, TENDL-2019, IRDFF-1.05, JENDL-4.0, and JEFF-3.3. The obtained cross section results are in good agreement with existing experimental data, evaluated libraries, and reaction models for the highest energy points (2.11 and 3.13 MeV), while the lowest-energy point at 0.61 MeV underestimates them.

The status of air quality in Kampala city, Uganda 2017-2019: Results from the Eastern Africa GEOHealth Hub using a high-tech reference monitor (Beta Attenuation Monitor 1022)

Introduction: Ambient air pollution (AP), particularly from fine particulate matter <2.5 micrometers in aerodynamic diameter (PM2.5) is a big public health problem especially in low and middle-income countries. Because of apparent high population growth rate (3%) and economic development in Uganda, ambient AP appears to be rising. As such, we are monitoring ambient PM2.5 concentrations in Kampala City in a series of studies about the effect of AP on health. This work is part of research and training objectives of the Global Environmental and Occupational Health (GEOHealth) Hub for Eastern Africa. Methods: Using a Beta Attenuation Monitor (BAM) 1022, we prospectively measured ambient PM2.5 concentration for 2 years. This equipment was installed at Makerere University School of Public Health building rooftop (about 15 meters high). The BAM 1022 generated real-time data on PM2.5, relative humidity and ambient temperature. Results: For the last two years (October 2017 to September 2019), the annual mean of PM2.5 concentrations were 41.3µg/m3 and 39.2µg/m3 respectively. Our two-year data consistently show that dry seasons (January, February, June, July and August) have higher monthly mean PM2.5 concentrations (46.6µg/m3) compared to the wet seasons of March, April, May, September-, October, November and December (35.7µg/m3). We observed that for two years the highest PM2.5 concentration in typical day was between 06.00hrs and 10.00hrs (peak being at 08.00hrs -PM2.5 61.3µg/m3). However, nights were more polluted between 19.00hrs to 04.00hrs (peak being at 23.00hrs (PM2.5 71.2 µg/m3). Further, when we divided the day (07.00hrs-18.00hrs) and night (19.00-06.00hrs), the average PM2.5 concentrations for the two years were 34.5µg/m3 and 46.9µg/m3 respectively.Conclusion: Ambient AP is higher in the dry season. Besides, there is more PM2.5 concentration at night compared to daytime. These results present an opportunity for further studies on AP and its effect on health using hospital mortality and morbidity data.

IGNORE: A Policy Server to Prevent Cyber-Attacks from Propagating to the Physical Domain

We present the intelligent governor for the smart grid system (IGNORE) to limit the success of attacks when a grid’s cyber system has been compromised and leveraged by an adversary to mount attacks on the physical system. IGNORE is based on the concept of the security reference monitor. It is a component that serves to protect a system from attacks that are more severe and frequent than is acceptable by enforcing security policies on the actions of the system’s higher-level functions. It enforces security and safety policies by ignoring commands issued by a system’s higher-level functions if by executing those commands may cause violations of its security and safety constraints. The underlying principle for generating security policies is the requirement and safety property that evaluates whether commands issued by a cyber system are required and safe in/for the physical system. Our key contribution is to present the methodology to design a governor for a grid’s higher-level function, that is, demand response. We define a set of attacks prevented by the governor, a set of rules that define the governor, and demonstrate its effectiveness through empirical results. This work sheds light upon how a higher-level functionality of a smart grid system is protected by analyzing the system’s cyber and physical aspects even when some parts of the cyber system are compromised.

Development of a multiple regression model to calibrate a low-cost sensor considering reference measurements and meteorological parameters.

Low-cost air quality sensors are widely used to improve temporal and spatial resolution of air quality data. In Lima, Peru, only a limited number of reference air quality monitors have been installed, which has led to a lack of data for establishing environmental and health policies. Low-cost technology is promising for developing countries because it is small and inexpensive to operate and maintain. However, considerable work remains to be done to improve data quality. In this study, a low-cost sensor was installed with a reference monitor station as the first stage for the calibration process, and a multiple regression model was developed based on reference measurements as an outcome variable using sensor data, temperature, and relative humidity as the predictive parameters. The results show that this particular technology exhibits a promising performance in measuring PM2.5 and PM10 (particulate matter with diameter aerodynamic less than 2.5μm and 10μm, respectively); however, the correlation for PM2.5 appears to be better. Temperature and relative humidity data from the sensor were only partially analyzed due to the evident low correlation with the reference meteorological data. The objective of this study is to begin analyzing the performance of low-cost sensors that have already been introduced to the Peruvian market and selecting those that perform better to provide for informed decision-making.

Translational data analytics in exposure science and environmental health: a citizen science approach with high school students

BackgroundTranslational data analytics aims to apply data analytics principles and techniques to bring about broader societal or human impact. Translational data analytics for environmental health is an emerging discipline and the objective of this study is to describe a real-world example of this emerging discipline.MethodsWe implemented a citizen-science project at a local high school. Multiple cohorts of citizen scientists, who were students, fabricated and deployed low-cost air quality sensors. A cloud-computing solution provided real-time air quality data for risk screening purposes, data analytics and curricular activities.ResultsThe citizen-science project engaged with 14 high school students over a four-year period that is continuing to this day. The project led to the development of a website that displayed sensor-based measurements in local neighborhoods and a GitHub-like repository for open source code and instructions. Preliminary results showed a reasonable comparison between sensor-based and EPA land-based federal reference monitor data for CO and NOx.ConclusionsInitial sensor-based data collection efforts showed reasonable agreement with land-based federal reference monitors but more work needs to be done to validate these results. Lessons learned were: 1) the need for sustained funding because citizen science-based project timelines are a function of community needs/capacity and building interdisciplinary rapport in academic settings and 2) the need for a dedicated staff to manage academic-community relationships.

Accuracy of blood-pressure monitors owned by patients with hypertension (ACCU-RATE study): a cross-sectional, observational study in central England.

BackgroundHome blood-pressure (BP) monitoring is recommended in guidelines and is increasingly popular with patients and health professionals, but the accuracy of patients’ own monitors in real-world use is not known.AimTo assess the accuracy of home BP monitors used by people with hypertension, and to investigate factors affecting accuracy.Design and settingCross-sectional, observational study in urban and suburban settings in central England.MethodPatients (n = 6891) on the hypertension register at seven practices in the West Midlands, England, were surveyed to ascertain whether they owned a BP monitor and wanted it tested. Monitor accuracy was compared with a calibrated reference device at 50 mmHg intervals between 0–280/300 mmHg (static pressure test); a difference from the reference monitor of +/−3 mmHg at any interval was considered a failure. Cuff performance was also assessed. Results were analysed by frequency of use, length of time in service, make and model, monitor validation status, purchase price, and any previous testing.ResultsIn total, 251 (76%, 95% confidence interval [95% CI] = 71 to 80%) of 331 tested devices passed all tests (monitors and cuffs), and 86% (CI] = 82 to 90%) passed the static pressure test; deficiencies were, primarily, because of monitors overestimating BP. A total of 40% of testable monitors were not validated. The pass rate on the static pressure test was greater in validated monitors (96%, 95% CI = 94 to 98%) versus unvalidated monitors (64%, 95% CI = 58 to 69%), those retailing for >£10 (90%, 95% CI = 86 to 94%), those retailing for ≤£10 (66%, 95% CI = 51 to 80%), those in use for ≤4 years (95%, 95% CI = 91 to 98%), and those in use for >4 years (74%, 95% CI = 67 to 82%). All in all, 12% of cuffs failed.ConclusionPatients’ own BP monitor failure rate was similar to that demonstrated in studies performed in professional settings, although cuff failure was more frequent. Clinicians can be confident of the accuracy of patients’ own BP monitors if the devices are validated and ≤4 years old.

Comparative Analysis of a Non-contact Respiratory and Heart Rate Monitor Vs. a Conventional Clinically Validated Reference Monitor

Comparative Analysis of a Non-contact Respiratory and Heart Rate Monitor Vs. a Conventional Clinically Validated Reference Monitor