Accuracy Of Device Research Articles

Quantitative analysis of cannabinoids and metabolites in oral fluid by volumetric absorptive microsampling combined with UHPLC-HRMS.

With recent evolution of cannabis legalization around the world and multiplication of cannabis derived products, identifying and qualifying cannabis consumption has a proven interest. Although blood, plasma, and urine are common matrices widely used in toxicology laboratories, oral fluid presents specific advantages. In the context of doping tests, addiction consultation or roadside checks, where other matrices are impractical to collect or can be adulterated, oral fluid is a promising matrix that allows a non-invasive, rapid, and monitored self-sampling. However, available devices required a consequent volume of oral fluid,more than 250 µL, sometimes difficult to collect. We present here a fully optimized quantitative method for seven cannabinoids, including four metabolites, in oral fluid, Δ9-tetrahydrocannabinol, 11-hydroxy-Δ9-tetrahydrocannabinol and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol; cannabidiol, 7-hydroxy and 7-carboxycannabidiol; and cannabinol. After self-collection of 20 µL using an accurate and precise volumetric absorptive microsampling device (VAMS®), cannabinoids were derivatized with 2-fluoro-1-methylpyridinium p-toluenesulfonate to increase sensitivity. The successive steps of the proposed method, including biosampling, 1 h sample preparation with derivatization, and acquisition by ultrahigh-performance liquid chromatography coupled to high-resolution mass spectrometry, were fully optimized. A limit of quantification of 0.5 ng/mL (≈10 pg per sampling) was thus targeted, adapted to the legal threshold required by the authorities and to clinical monitoring. Applied to six cannabis consumers, the proposed method made it possible to quantify in 20 µL oral fluid samples, Δ9-tetrahydrocannabinol ranging from 0.5 to 6236 ng/mL, cannabidiol from 0.6 to 190 ng/mL and cannabinol from 0.5 to 118 ng/mL.

A Low-Cost Ultrasonic Sensor for Online Monitoring of Water Levels in Rivers and Channels

The measurement of flow parameters in rivers and channels is essential for anticipating floods, hydraulic modeling, and conducting water resource management studies. However, the high cost of existing equipment has resulted in a shortage of monitoring stations compared to actual requirements. This research focused on developing and validating a low-cost, highly accurate ultrasonic device that minimizes malfunctions for online monitoring of water levels in channels and streams. Considering the availability of components, cost, and the reported resolution of the product, the GY-Us42 sensor was selected for constructing the level gauge. The sensor operates within a range of 20 cm to 720 cm with a measurement accuracy of approximately 1 mm. The device integrates several error reduction mechanisms to enhance accuracy, including averaging multiple readings and temperature correction techniques. Laboratory data and field data gathered by both staff and shaft encoder were used for device validation. After constructing the main prototype and conducting various tests, multiple devices were installed in different locations within the Tehran rivers, and water depth data were collected over a specific period. Subsequently, data from other field sensors were also collected and used for device validation and accuracy assessment. The results indicate that the device's average error is below 3%, with a Root Mean Squared Error (RMSE) of 5.00 cm during field tests, demonstrates that the constructed device is an efficient tool for measuring water levels in streams, particularly during flood events.

Design and analysis of terrestrial laser scanner based on a 3-SPR parallel mechanism for improved anti-occlusion scanning

Abstract Laser scanner technology swiftly captures point cloud data of objects and their surrounding environments, proving extensive applications across various sectors. However, it often encounters challenges related to incomplete point clouds due to occlusion from stationary objects. This paper presents a terrestrial laser scanning system based on a 3-SPR (3-Spherical Joint-Active Prismatic Joint-Rotating Joint) parallel mechanism (TLS-PM), specifically designed to enhance scanning coverage during single-station measurements, reduce positioning and workload during multi-station measurements, and mitigate point cloud gaps caused by occlusions.
Initially, a simulation model of the TLS-PM was developed, and both forward and inverse kinematic analysis were performed. Subsequently, the workspace was computed for different spherical joints using this model. An introduction to the TLS-PM’s error and the registration algorithm employed was then provided. Finally, through comparative analysis of simulations and experimental results, the device's measurement accuracy and its capability to resist occlusions were validated. Additionally, the TLS-PM’s anti-occlusion performance was evaluated under various scenarios in a simulated setting. The experimental results demonstrate that, when employing the same conventional point cloud processing algorithms, the TLS-PM significantly improves the background scanning coverage.

Fabric-based visualization biosensor for real-time environmental monitoring and food safety

Foodborne and waterborne bacterial infections caused by Escherichia coli (E. coli) pose a serious threat to public health and safety. Therefore, there is an urgent need to develop a fast and accurate diagnostic device for early detection and prevention of bacterial contamination. In this study, we designed a visual cotton fabric-based detection biosensor that can target enzymes produced by E. coli metabolism and induce color changes. In addition, the system can be integrated with the naked eye, smartphones, and small spectrometers to analyze the generated signals for qualitative, semi-quantitative, and quantitative detection. The platform achieved a minimum detection limit of 537 cfu/mL for E. coli, a wide detection range of 102-106 cfu/mL, and a minimum detection time as low as 20 mins. The detection results of complex environmental samples showed that the system has excellent anti-ion interference and anti-pH interference behavior. This visual detection biosensor has great commercial application potential and can be widely used in real-time on-site detection due to its rapid, portable, anti-interference, and low-cost advantages.

DRBD-YOLOv8: A Lightweight and Efficient Anti-UAV Detection Model.

Interest in anti-UAV detection systems has increased due to growing concerns about the security and privacy issues associated with unmanned aerial vehicles (UAVs). Achieving real-time detection with high accuracy, while accommodating the limited resources of edge-computing devices poses a significant challenge for anti-UAV detection. Existing deep learning-based models for anti-UAV detection often cannot balance accuracy, processing speed, model size, and computational efficiency. To address these limitations, a lightweight and efficient anti-UAV detection model, DRBD-YOLOv8, is proposed in this paper. The model integrates several innovations, including the application of a Re-parameterization Cross-Stage Efficient Layered Attention Network (RCELAN) and a Bidirectional Feature Pyramid Network (BiFPN), to enhance feature processing capabilities while maintaining a lightweight design. Furthermore, DN-ShapeIoU, a novel loss function, has been established to enhance detection accuracy, and depthwise separable convolutions have been included to decrease computational complexity. The experimental results showed that the proposed model outperformed YOLOV8n in terms of mAP50, mAP95, precision, and FPS while reducing GFLOPs and parameter count. The DRBD-YOLOv8 model is almost half the size of the YOLOv8n model, measuring 3.25 M. Its small size, fast speed, and high accuracy combine to provide a lightweight, accurate device that is excellent for real-time anti-UAV detection on edge-computing devices.

Comparing the accuracy of 3D urban olive tree models detected by smartphone using LiDAR sensor, photogrammetry and NeRF: a case study of ’Ascolana Tenera’ in Italy

Abstract. Rapid urban growth makes green space management crucial to improve citizens’ well-being. Urban olive trees characterize the Italian landscapes and their culture. This study explores different methodologies for urban tree assessment in this context, using an iPhone 14 Pro Max. These included: 1) its integrated Light Detection and Ranging (LiDAR) sensor using the Recon3D app, 2) its camera with Structure from Motion (SfM) techniques, and 3) its camera for generating 3D models using Neural Radiance Fields (NeRF). Additionally, a professional Mobile Laser Scanner (MLS), was used for comparison. Total height (H), canopy base height (CBH) and canopy volume (CV) measurements were extracted using both CloudCompare and allometric formulas. The main aim of this paper is to compare the 3D models of olive trees obtained from low-cost sensors with those generated from the MLS, which is a more accurate device but comes with significantly higher costs. The results, in terms of RMSE (iPhone LiDAR - H: 0.46 m, CBH: 0.12 m, CV: 15.66 m3; iPhone-SfM - H: 0.95 m, CBH: 0.19 m, CV: 25.85 m3; iPhone-NeRF - H: 1.26 m, CBH: 0.31 m, CV: 33.79 m3), bias and volume differences, reveal that the smartphone, in all the methodologies, tends to underestimate measurements as the size of the trees increases. This is due to the higher MLS range of acquisition. Despite these limitations, low-cost solutions like smartphone-based methods can be a viable alternative given their economic accessibility.

WACARDIA: Graphical MATLAB software for Wireless Assessment of CARDiac Interoceptive Accuracy

Many theories of psychological function emphasize the importance of bodily sensations and the ability to accurately detect them, known as interoceptive accuracy. The most common measure of interoceptive accuracy uses heartbeat detection tasks such as the Whitehead Task, yet to our knowledge there are no freely accessible programs to conduct this task. In this paper, we present novel software called WACARDIA (Wireless Assessment of CARDiac Interoceptive Accuracy), which is free, open-source software that conducts the heartbeat detection task using Matlab and Psychtoolbox. WACARDIA contains several key features supporting participant engagement, operator convenience, and measurement accuracy. First, the program includes an optional practice trial of unlimited duration, a participant-facing graphical interface, and the ability to perform heartbeat detection training. Second, the operator is provided with a graphical user interface, live trial feedback, an accurate wireless electrocardiogram device, and a separate program to conduct the related Heartbeat Tracking task. Finally, the program ensures the accuracy of collected data by scheduling the delivery of tones with high precision and implementing fail-safes to automatically reset erroneous measurements. This paper includes flowcharts that help create transparency by describing our algorithm. We also outline customizable aspects of the program with the intent to have WACARDIA’s algorithm expanded to accommodate more situations and applications. With this paper, we hope to encourage the practice of publicizing research software to contribute to the transparency, rigor, and reproducibility of scientific studies. WACARDIA and video tutorials are available at www.github.com/iankleckner/wacardia and http://wacardia.iankleckner.com.

Design and analysis of power decoupling based microinverter considering parasitic parameters

With fossil energy reducing year by year, more and more attention to the new energy sources greatly promotes the development of the distributed power generation system, especially the low-power photovoltaic system. However, the power injected into the single-phase grid is time-varying, an electrolytic capacitor with large bulk should be paralleled with PV to balance the input and output power ripple. But the electrolytic capacitor has a very short lifetime, which could shorten the whole inverter’s lifetime. In this paper, the operational principle of the power decoupling based microinverter considering parasitic parameters is proposed, in which a film capacitor with small capacitance value replaces the electrolytic capacitor to improve the lifetime of the inverter. Further, the operating mode of the transformer and the decoupling capability is analyzed, and obtains the reasons affecting the inverter steady-state performance. Finally, the simulation and experiment validation of the proposed microinverter have been accomplished. Base on the analysis method proposed in this paper, a more accurate device selection can be provided for industrial design.

Feasibility, accuracy, and reproducibility of device sizing in virtual reality for percutaneous left atrial appendage closure - a single center study

Abstract Background Left atrial appendage closure (LAAC) is a safe and effective procedure for stroke prevention in patient with non-valvular atrial fibrillation. Procedural planning and device sizing remains challenging due to the highly complex and variable three-dimensional (3D) anatomy of the left atrial appendage (LAA). Virtual reality (VR) is a innovative, recent technology allowing a superior spatial orientation visualization of 3D imaging datasets. Purpose Therefore, we aimed to evaluate feasibility and accuracy of LAA measurements in VR for device sizing in patients planned for LAAC. Methods Twenty-one patients (79±7 years, 62% male) with non-valvular atrial fibrillation scheduled for LAAC were randomly included in our study. Preprocedural a multi-slice computed tomography (MSCT) was performed for device sizing in all patients. MSCT-based 3D models were established and visualized in VR using a dedicated software (VMersive, Warsaw, Poland). LAA dimensions (Ostium, landing zone (LZ), and depth) were assessed directly in the virtual environment. Conventional measurements of LAA ostium, landing zone (LZ) and depth using commercially available software were compared to measurements in VR. Results 3D reconstruction of MSCT datasets and visualization in VR were successfully performed automatically in all patients within a few seconds. MSCT and VR demonstrated good correlations for ostium minimum (r = 0.93), maximum (r = 0.8) and mean (r = 0.88, all p<0.001) diameters. Additionally, LZ minimum (r=0.84), maximum (r=0.86) and mean (r=0.9) diameters showed good correlation (all p<0.001). Moderate correlation was observed for depth measurements (r=0.76, p<0.001). Furthermore, intraclass correlation coefficients ranging from 0.88 to 0.98 denoted high inter- and intraobserver agreement. Conclusion Immersive VR allows highly feasible, accurate and reproducible measurements of the LAA dimensions directly in the virtual environment, hence enabling accurate device sizing for LAAC.

Use of a Microelectromechanical Systems Sensor for Objective Measurements of Abnormal Head Posture in Congenital Superior Oblique Palsy Patients.

The purpose of this study was to design an objective method for measurement of head positions as achieved with use of a microelectromechanical systems (MEMS) sensor. In addition, to use this system to observe the abnormal head position (AHP) in patients with congenital superior oblique palsy (SOP) before and after their surgery. An MEMS sensor was designed for recording of the pitch, roll, and yaw values of the head position in real time. The MEMS sensor was then fixed on the synoptophore from -30 degrees to +30 degrees positions horizontally and vertically to test the accuracy of these measurements. Then, we tested 13 participants with AHP using the MEMS method and the photographic method and compared their correlations. Finally, the pitch, roll, and yaw values of head positions were measured using this MEMS sensor in 31 patients with congenital SOP as performed before and after their surgery. The MEMS sensor (LPMS-B2; Alubi, Guangzhou, China; 400 hertz [Hz]), as based on the theory of a gyroscope, was designed and connected to a smartphone via Bluetooth. It was able to conveniently record the patient's pitch, roll, and yaw head positions in real time, recordings which were consistent with the scales of the synoptophore (P > 0.05) and good correlations with the photographic method (P < 0.001). The main preoperative AHP in patients with SOP was roll (22/31, 71%). Pre- and postoperative vertical deviations were 16.4 ± 7.3 prism diopters (PD) and 4.1 ± 4.2 PD, respectively (P = 0.001). The AHP in patients with SOP was positively correlated with the angle of extorsion in the dominant eye (P = 0.01), rather than that of the vertical deviation. The MEMS sensor described in this report is a simple, practical, and accurate objective device for use in head position measurements. In patients with SOP, the AHP is related to the angle of extorsion in the dominant eye. The MEMS sensor was designed as a micro-wireless dynamic high-precision device for AHP measurement, which has the potential for use in a clinic.

A ring resonators optical sensor for multiple biomarkers detection

In the recent years, the number of Point-Of-Care-Tests (POCTs) available for clinical diagnostic has steadily increased. POCTs provide a near-patient testing with the potential to generate a result quickly so that appropriate treatment can be implemented, leading to improved clinical outcomes compared to traditional laboratory testing. Technological advances, such as miniaturization of sensors and improved instrumentation, have revolutionized POCTs, enabling the development of smaller and more accurate devices. In this context, it has also gained increasing importance the screening of various analytes simultaneously to increase specificity and improve the characterization of the disease. This study is aimed at developing and characterizing a photonic integrated circuit for multiple markers detection, which represents the functional core towards a full developed POCT device for clinical pathology applications. The photonic sensor, based on microring resonators (MRRs), is functionalized by immobilizing specific antibodies on a copolymer layer deposited on the MRR’s surfaces. Surface chemical techniques were employed to analyse the surface chemical characteristics while fluorescence microscopy was involved to analyse the resulting bioreceptor surface density. The photonic sensor is characterized for the parallel detection of two biomarkers, the C-Reactive Protein (CRP) and the Creatine-Kinase-MB (CK-MB). The analyte-antibody binding curves were obtained both in buffer and in filtered un-diluted artificial saliva showing promising results both in terms of sensitivity, with limit of detection (LOD) of 103 pM for CRP and 140 pM for CK-MB, and in terms of specificity. These encouraging results let the assembly of a highly sensitive POC device for molecular diagnostics.

Understanding Standard Procedure in Auditory Brainstem Response: Importance of Normative Data.

The auditory brainstem response (ABR) is a noninvasive test that measures neural activity in response to auditory stimuli. Racial differences in head shape have provided strong evidence for specific normative data and accurate device calibration. International standards emphasize the need for standardized procedures and references. This study aimed to outline the standard procedure and related normative ABR values. Standard procedures were performed according to International Electrotechnical Commission (IEC) standards. Five studies from two countries were included to compare the normative values of the ABR. The dataset from the National Standard Reference Data Center (NSRDC) was used as reference. Normative values were described in terms of stimuli, latency, and amplitude. For click stimuli, the latency of the ABR showed different patterns across populations, such as those from Korea and the USA. Although the latencies reported by the NSRDC and for Koreans were relatively short, those reported for USA populations were longer. Using clicks, it was shown that the USA population had the largest ABR amplitude compared to those reported for the other two datasets. For Wave V latency using tone bursts, a similar pattern was identified with click stimuli. Frequency-specific trends were also observed. Although there is a lack of ABR datasets, the information and insights of the present study could be utilized as standard guidelines in research on ABR.

Detection of hypertension using a target spectral camera: a prospective clinical study

Hypertension is a significant contributor to premature mortality, and the regular monitoring of blood pressure (BP) enables the early detection of hypertension and cardiovascular disease. There is an urgent need for the development of highly accurate cuffless BP devices. We examined BP measurements based on a target spectral camera’s recordings and evaluated their accuracy. Images of 215 adults’ palms and faces were recorded, and BP was measured. The camera captured RGB wavelength data at 640 × 480 pixels and 150 frames per second (fps). These recordings were analyzed to extract pulse transit time (PTT) values between the face and palm, a key parameter for estimating BP. Continuous BP measurements were taken using a CNAPmonitor500 for validation. Three frequency wavelengths were measured from video images. A machine learning model was constructed to determine hypertension, defined as a systolic BP of 130 mmHg or higher or a diastolic BP of 80 mmHg or higher, using the visualized data. The discrimination between hypertension and normal BP was 95.0% accurate within 30 s and 90.3% within 5 s, based on the captured images. The results of heartbeat-by-heartbeat analyses can be used to determine hypertension based on only one second of camera footage or one heartbeat. The data extracted from a video recorded by a target spectral camera enabled accurate hypertension diagnoses, suggesting the potential for simplified BP monitoring.

A 291-day Evaluation of the Performance of a Consumer-grade Temporal Radon Detector.

Affordable, accurate, and robust temporal measurement devices are desirable for screening and assessment of radon levels in private homes and workplaces. This research expands upon prior research, using the RadonFTlab RadonEye device through a comparison of multiple samples of this instrument with a laboratory-grade instrument, the Saphymo AlphaGUARD, over a more extensive period than reported previously. Data were collected over 291 d in a poorly ventilated basement space in an occupied building. Environmental conditions varied naturally, changing both the radon source term and radon entry into the space approximating typically deployed conditions. The R-squared linear regression correlation coefficient and relative sensitivities of each RadonEye with the AlphaGUARD were computed. Overall temporal and diurnal variations were also studied. The sensitivities of all RadonEyes and the AlphaGUARD agreed to within 22% throughout the entire deployment period.

The Time Is Ripe: Olive Drupe Maturation Can Be Simply Evidenced by a Miniaturized, Portable and Easy-to-Use MicroNIR Green Sensor

The analytical study described in this work, based on NIR spectroscopy with a handheld device, allowed the development of a chemometric prediction model that has been validated for the objective evaluation of the ripening of olive drupes. The miniaturized, portable NIR spectrometer is proposed here as an easy-to-use sensor able to estimate the best harvesting time for ripening of olive drupes. The MicroNIR/chemometrics approach was developed for on-site identification of olive drupe ripening directly on plants, avoiding collection and successive laboratory analysis steps. A supporting parallel characterization by chromatographic techniques validated the spectroscopic prediction. The novelty of this approach consists in the possibility of investigating the olive drupe maturation point by collecting spectra in the near-infrared region and processing them using a chemometric model. The fast and accurate device allows one to easily follow the spectrum profile changes of olive drupes during ripening, thus preserving the fruits from being harvested too early or too late. The results of this study demonstrate the possibility of using the MicroNIR/chemometrics approach to determine the optimal ripening time of olives regardless of the plant variety, age and cultivation location. The results consequently demonstrated that the MicroNIR/chemometrics approach can be proposed as a new method to perform on-site evaluation of ripening by a single-click device. It can be conveniently used by any operator, who does not necessarily have to be expert but must simply be trained to use spectroscopy and a prediction model.

Development of tongue strength and endurance measurement device: A pilot study in healthy adults

Background: Safe and efficient swallowing relies on adequate tongue strength and endurance. Thus, tongue strength and endurance assessments are essential for swallowing rehabilitation for individuals with swallowing difficulties due to tongue structure and function abnormalities. These tongue functions can be objectively measured using a standard device. However, in Thailand, assessing tongue strength and endurance using standard devices is not widespread in clinical practice due to the high cost of importing these devices. Objective: This study aimed to develop a precise, accurate, and reliable tongue function measurement device for the clinical assessment of tongue strength and endurance. Materials and methods: This study was divided into three phases: 1) Development of a tongue strength and endurance measurement device in a laboratory setting and administration of a satisfaction questionnaire, 2) Trial of the prototype device with six participants, and 3) Assessment of the test-retest reliability of the developed device and investigation of tongue strength and endurance values with twenty participants. Results: As a result of this development, a novel device for measuring tongue strength and endurance was obtained, which provides measurements in units of newtons (N) and kilopascals (kPa) for strength and seconds (s) for endurance. The device’s development cost was significantly lower compared to imported commercially available devices while maintaining the performance standards for medical measurement devices. This was demonstrated by its accuracy ranging from 96.40% to 100%, high precision with a Coefficient of Variation (% CV) of 0.90% to 4.21%, and moderate to excellent reliability with an Intraclass Correlation Coefficient (ICC) of 0.56 to 0.93. Furthermore, statistically significant differences (p&lt;0.01) were observed between genders, especially in anterior tongue strength. Conclusion: The tongue strength and endurance measurement device developed through this study can be utilized for clinical tongue function assessment, giving patients more access to objective evaluations of tongue strength and endurance at a lower examination cost.

Augmented Reality-Based Chronic Wound Healing Assessment Using 3D Stereoscopic Imaging and Self-Organizing Maps

Background: Chronic wounds (CW) present significant public health challenges, impacting individuals' well-being and daily activities. Traditional wound measurement methods, such as the ruler technique, are time-consuming, imprecise, and pose infection risks. Advances in wound care technology, including artificial intelligence (AI) and augmented reality (AR), have improved wound healing (WH) assessment accuracy and enhanced clinician-patient communication. Methods: This study developed a novel CW evaluation device combining AR and a stereoscopic camera system. The device captures images using two Leopard Imaging LI-OV580 stereo cameras and a pico-projector to create a 3D wound model. The system calculates the wound area by processing stereoscopic images, utilizing structured-from-motion techniques and convolutional neural networks (CNNs). Additionally, the device measures epipolar and projection errors (PE) during AR-based wound evaluation. A Self-Organizing Map (SOM) was employed to refine the 3D reconstruction of the wound. Results: The AR-PE analysis demonstrated the device's accuracy, with the lowest PE recorded at 20 cm from the wound area. The projection error increased as the measurement distance moved toward the edges of the wound. The average epipolar error (EE) was 0.46 pixels, indicating high precision in stereoscopic measurements. Conclusion: The study introduced a non-invasive CW evaluation device that improves wound assessment accuracy and clinician-patient interaction. By utilizing 3D wound modeling and AR, the system enables more effective communication and progress tracking during WH. The results suggest this technology could enhance CW management, offering a reliable alternative to traditional methods.

P066 HOW BLOOD PRESSURE DEVICES ARE OBTAINED FOR HOME BLOOD PRESSURE MEASUREMENT: A MIXED-METHODS STUDY AMONG AUSTRALIA ADULTS

Background and Objective. Only 20% of automated blood pressure (BP) devices available for purchase are validated. However, how consumers obtain devices for home BP measurement and whether their devices are validated remains unknown, which was the aim of this study. Methods. Surveys (n=225) and interviews (n=27) among adults who measure BP at home in Australia (June-December 2023). Survey questions included how the BP device was obtained, device details to determine validation status, and considerations in choosing a device. Interviews explored how and why BP devices were obtained in detail. Results. Most participants (n=216, 96%) used an upper-arm cuff device, of which 52% (n=118) were validated. Of 9 participants that used wrist cuff devices, 67% (n=6) were validated. Most participants purchased (n=176, 91%) their BP device, predominantly from pharmacy (n=126, 72%; 50% validated), followed by online (n=36, 16%; 52% validated). Validated BP devices were on average $38.53 AUD more expensive than non-validated devices (p&lt;0.001). Although accuracy was the most important consideration when choosing a BP device (n=112, 50%), few interview participants cited device validation status as a consideration. “I just assumed that they were all accurate”. Most interview participants avoided cheaper BP devices, believing these were less accurate, and they were willing to “make an investment” in their BP device due to the importance of getting an accurate BP measurement. Interview participants rarely received recommendations from their GP about which BP device to use and reported pharmacy staff provided retail support based on in-store device availability rather than information about accuracy. Conclusion. This study found only 50% of devices used by consumers for home BP measurement have been validated. Devices that are validated are more expensive, but critically, consumers are willing to make an investment in an accurate BP device. However, little guidance is provided to support consumers when selecting a BP device. These findings demonstrate the need for credible information and resources that support consumers to obtain validated BP devices.

Research on the Key Technology of a Fluorescence Detection Device Using the RT-LAMP Method for Instant Detection.

As of 31 October 2023, there have been 771,795,258 confirmed cases of COVID-19 globally. Developing simple, portable, and reliable testing devices has become increasingly important. This paper presents a point-of-care testing (POCT) device for COVID-19 based on the dual-excitation fluorescence RT-LAMP method, which is derived from the principles of RT-LAMP-based COVID-19 detection kits available in the market. The key design solutions of the device were simulated and modeled. Key performance metrics such as detection repeatability and linearity were validated. Comparative experiments with the RT-qPCR detection method were conducted to verify the accuracy and reliability of the device. Additionally, the device's detection sensitivity and accuracy were assessed. Experimental results show that the repeatability coefficient of variation (CV) value is ≤0.09%; the linearity R2 for the FAM channel is 0.9977 and that for the HEX channel is 0.9899; it exhibits good anti-interference performance, with negligible cross-channel interference; the temperature stability is ±0.062 °C, the temperature accuracy is less than 0.2 °C, and there is no significant temperature overshoot during the heating process. Compared with the real-time quantitative PCR (RT-qPCR) instrument, the positive agreement rate is 100% and the negative agreement rate is 95.0%. This research provides a foundational basis for the development of equipment for the prevention of infectious diseases and clinical diagnostics.

Cloud-based system for monitoring event-based hydrological processes based on dense sensor network and NB-IoT connectivity

Hydrologists claim high-quality experimental data are required to improve the understanding of hydrological processes. Though accurate devices for measuring hydrological processes are available, the on-site deployment and operation of effective monitoring networks face many relevant issues caused by the peculiar characteristics of hydrological systems. In this manuscript, we present a self-developed system for monitoring events-based hydrological processes comprising a dense network with both soil moisture and water level gauges connected by NB-IoT technology integrated into a cloud system for near real-time gathering of information. We designed, built and calibrated the sensors and integrated them into a cloud system. We deployed them in two monitoring networks and gathered the data from several experimental runs (battery lifecycles). Results showed the suitability of the sensors and the network to properly monitor the processes solving the initial relevant issues mainly derived from connectivity issues and battery duration.