Real-time Device Research Articles

Use of Continuous Glucose Monitors to Manage Type 1 Diabetes Mellitus: Progress, Challenges, and Recommendations.

Type 1 diabetes (T1D) management has been revolutionized with the development and routine utilization of continuous glucose monitoring (CGM). CGM technology has allowed for the ability to track dynamic glycemic fluctuations and trends over time allowing for optimization of medical therapy and the prevention of dangerous hypoglycemic events. This review details currently-available real-time and intermittently-scanned CGM devices, clinical benefits, and challenges of CGM use, and current guidelines supporting its use in the clinical care of patients with T1D. We additionally describe future issues that will need to be addressed as CGM technology continues to evolve.

High-sensitivity integrated detector with nanostructured hydrogel electrode for ascorbic acid determination

This paper proposed a novel integrated detector with nanostructured hydrogel electrode (IDNHE) for ascorbic acid detection. The electrochemical detector was integrated on printed circuit board (PCB). The IDNHE employed the nanostructured multi-walled carbon nanotubes/polyaniline/polyvinyl alcohol (MWCNTs/PANI/PVA) hydrogel as the working electrode. The PVA hydrogel can not only effectively combine the PANI and substrate through hydrogen bonds, but also greatly improve the stability and durability of the detector. MWCNTs were used to fabricate the nanostructures, increasing the surface area of electrode. The detection mechanism is based on the redox reaction of PANI with ascorbic acid. The detection limit and the sensitivity of IDNHE were 0.9 μM (S/N = 3) and 161.46 mA·μM−1·cm−2, respectively. Moreover, IDNHE has a satisfactory reproducibility (RSD = 1.43 %), repeatability (RSD = 2.35 %) and long-term stability for 90 days. Therefore, this work undoubtedly provides a considerate choice for the lab on a chip, and further a promising application prospect for developing the portable real-time monitoring device.

Modeling and implementation of a low-cost IoT-smart weather monitoring station and air quality assessment based on fuzzy inference model and MQTT protocol.

The automatic weather system serves to inform farmers, tourists, planners, and others with precise information to help them take the appropriate action. Today, with the advancement of smart technologies, the system has evolved into many sensing methods to gather real-time climate data. Thisarticleinvestigatesthemodelingandimplementationofalow-cost weatherstationdevicethatalsofunctions to measureairquality. The proposed system based on the Internet of Things (IoT) allows access to real-time climate data for a given area. This system monitors environmental conditions such as ambient temperature, humidity, atmospheric pressure, altitude, and levels of harmful atmospheric gases like CO2 and NO2. This real-time telemetry device uses MQ-135, DHT-11 and BMP280 sensors to gather data. The ESP32 board processes the obtained data from all sensors. Additionally, we present a model for a fuzzy inference system (FIS) that performs parameter categorization using a reasoning procedure and incorporates the results into an air quality index (AQI) that describes the levels of pollution for Al Hoceima city. The FIS takes CO2 and NO2 values as input and returns the AQI. The AQI for Al Hoceima city is categorized into six levels: Excellent, Good, Regular, Bad, Dangerous, and Very Dangerous. Furthermore, the suggested system's block hardware employs the Message Queuing Telemetry Transport (MQTT) protocol to broadcast collected data to a mobile and web application via the Internet. The suggested IoT-embedded device was tested in real life, and the results were promising.

Flexible CsPbCl3 inorganic perovskite thin-film detectors for real-time monitoring in protontherapy

Introduction: This paper deals with the class of versatile semiconducting materials called perovskites, which have been deposited for the first time on flexible substrates and then tested for radiation detection monitoring applications.Methods: Lead halide inorganic perovskite, CsPbCl3, 0.4–1 μm-thick films have been grown on plastic flexible substrates equipped with interdigitated electrodes (IDEs) by magnetron sputtering at room temperature.Results: First measurements in realtime configuration are reported for a 1–µm thick prototype under proton beams with energy in the range 100–228 MeV and 1–10 nA extraction currents, of interest for protontherapy applications.Discussion: Experimental results evidence good performances of our sample as a real-time monitoring device. Current stability under UV and proton beam exposure has been tested in the range 0.1–120 s, as well as reproducibility under multiple exposures. The measured current signal proved to be linearly dependent on the extraction currents at a given proton energy. Linearity of the current signal of the device with proton fluxes was also proved within two order of magnitude range, about 107–109 p/s. These promising results, when coupled with easyness of fabrication, low processing costs and high versatility of electrode configurations, all features characterizing the manufacturing process, put into evidence lead halide perovskites as promising candidates for real-time radiation detection in protontherapy.

Heat Transfer Simulation and Analysis of Electron Collector Based on Real-time Uniformity Detection Device of Irradiation Accelerator

Beam scanning uniformity is an important parameter of electron irradiation accelerators, which affects the quality of irradiated products. Accurate measurements of beam scanning uniformity are required to evaluate accelerator performance. Currently, a set of devices is being developed to measure beam scanning uniformity under full beam conditions. However, the measurement device faces serious heating problems when the beam power is large. In this paper, the cooling structure of the electron collector is designed for the developed measurement device. The temperature distribution of the electron collector is simulated by ANSYS. The appropriate cooling flow rates are selected to ensure the thermal stability of the device when the total beam powers are 30 kW and 50 kW, respectively. The electron collector with a cooling structure is fabricated according to design parameters, and the experiment is carried out under a 1.5 MeV accelerator. The temperature is monitored by an infrared thermometer. The results show that the measured temperature is below the limit. The designed cooling parameters effectively solve the heating problem.

Crankshaft Stress Telemetry Device and Its Low Power Strategy

In view of the fact that the crankshaft of an internal combustion engine lacks the support of measured stress data due to the closed working environment, a real-time stress test device for crankshaft and its low power strategy were studied. An embedded telemetry technology is used to solve the system miniaturization and low-power strategy. The integrated circuit chip is used to realize the miniaturization design, and a specialized power management scheme is designed to realize the low-power strategy. The actual test shows that the device can run continuously and stably under the environment of high temperature and oil pollution inside the crankcase and can record the stress curve of the crankshaft and transmit it to the remote computer in real time, which realizes the data visualization on the computer. The designed low-power strategy can help the device complete a single test period, and the device has higher promotion value and practical significance.

Recent Advance in Cortisol Immunosensing Technologies and Devices

Well known as the “stress hormone”, cortisol plays an indispensable role in life activities. In the past few decades, accurate information about the intracorporal level of cortisol has been proven to be an important and effective indicator for evaluating physical and mental states and diagnosing a series of pressure-induced diseases. Hence, various rapid and efficient cortisol sensing technologies with high sensitivity and selectivity and low detection limit have been developed. This review examines most recent works and progress in cortisol detection via immunoassay, highlighting the construction of sensitive sensor systems. We aimed to provide a comprehensive description in the aspects of general optical and electrochemical detection methods, novel immunosensing systems, and advanced portable and wearable devices. Outlooks and suggestions for the development of continuous and real-time monitoring techniques and devices were finally provided.

Axial and radial crushing behaviour of thin-walled carbon fiber-reinforced polymer tubes fabricated by the real-time winding angle measurement system

This paper proposed a real-time winding angle measurement device embedded in the portable 3-axis winding machine, which was used to detect and measure the winding angle during the winding process. The device was completely designed, fabricated, tested, and divided into hardware and software sections. The hardware section was adopted Raspberry Pi 3B+ and Arducam 5MP OV5647 camera modules, and the software section was used the OpenCV software. The experimental test was carried out to validate the measurement data on ±45°, ±60°, and ±75° winding angles, and filament-wound carbon fiber-reinforced polymer tubes were performed the quasi-static radial and axial compression tests. It was found that the real-time measurement data from the system had approximately 0.45±0.02 comparative error value than the targeted winding angle, which was more accurate than traditional measurement data. Moreover, it was shown that peak crushing loading significantly increased with increasing winding angle under radial compression, which had the inverse decreasing trend under axial loading. In addition, the crushing behaviour of thin-walled CFRP tubes was studied.

Real-time Navigation for Vascularized Lymph-node Transplantation Using Projection Mapping with Indocyanine Green Fluorescence.

The medical imaging projection system (MIPS) is a real-time surgical navigation device using indocyanine green (ICG) emission signals and active projection mapping. The difference between the object and the projected image is within 1 mm, and the time lag is within 0.1 seconds. We herein report the application of the MIPS to vascularized lymph-node transplantation (VLNT) surgery for lower extremity lymphedema to detect inguinal lymph nodes and perform color-coded navigation surgery for lymph-node resection. A left superficial inguinal lymph node was planned to be used as a donor for VLNT to the right lower leg in a 73-year-old woman with lower extremity lymphedema. Under general anesthesia, multiple intradermal injections of 0.1 ml of ICG were administered around the left inguinal donor site. The MIPS showed a clear linear projection image from a lateral injected point connecting to a lateral superficial inguinal lymph node. The left superficial circumflex iliac artery and vein were dissected for vascularized VLNT. Intraoperative real-time MIPS navigation continuously guided the transection plane colored by ICG fluorescence signals without shifting the visual focus from the surgical field. This is the first report of the intraoperative use of ICG projection mapping for VLNT donor-site surgery. The MIPS was able to visualize functional lymph nodes to facilitate minimally invasive donor-site surgery.

ROMI: A Real-Time Optical Digit Recognition Embedded System for Monitoring Patients in Intensive Care Units.

With advances in the Internet of Things, patients in intensive care units are constantly monitored to expedite emergencies. Due to the COVID-19 pandemic, non-face-to-face monitoring has been required for the safety of patients and medical staff. A control center monitors the vital signs of patients in ICUs. However, some medical devices, such as ventilators and infusion pumps, operate in a standalone fashion without communication capabilities, requiring medical staff to check them manually. One promising solution is to use a robotic system with a camera. We propose a real-time optical digit recognition embedded system called ROMI. ROMI is a mobile robot that monitors patients by recognizing digits displayed on LCD screens of medical devices in real time. ROMI consists of three main functions for recognizing digits: digit localization, digit classification, and digit annotation. We developed ROMI by using Matlab Simulink, and the maximum digit recognition performance was 0.989 mAP on alexnet. The developed system was deployed on NVIDIA GPU embedded platforms: Jetson Nano, Jetson Xavier NX, and Jetson AGX Xavier. We also created a benchmark by evaluating the runtime performance by considering ten pre-trained CNN models and three NVIDIA GPU platforms. We expect that ROMI will support medical staff with non-face-to-face monitoring in ICUs, enabling more effective and prompt patient care.

Experimental study on real-time measurement of single-event effects of 14 nm FinFET and 28 nm planar CMOS SRAMs based on Qinghai-Tibet Plateau

Based on the Yangbajing International Cosmic Ray Observatory in Lhasa with an altitude of 4300 m, a long-term real-time experiment is carried out in order to measure the atmospheric radiation induced soft errors in 14 nm FinFET and 28 nm planar CMOS SRAM array. The underlying mechanisms are also revealed. Five boards are used in the test, four of which are equipped with 28-nm process devices, and one board is equipped with 14-nm process devices. After removing the unstable bad bits, the actual effective test capacity is 7.1 Gb. During the test, the on-board FPGA reads the stored contents of all the tested devices in real time, reports the error information (occurrence time, board number, column number, device number, error address, error data) and corrects the error. The duration of the test is 6651 h. A total of 56 single event upset (SEU) events are observed, they being 24 single bit upset (SBU) events and 32 Multiple Cell Upset (MCU) events. Based on previous results of 65-nm SRAM, the study finds that SER continues to decrease with the reduction of process size, but the proportion of MCU in 28-nm process devices (57%) exceeds SBU, which is a process “maximum point” of MCU sensitivity, and the maximum size of MCU is 16 bits. Although the Fin spacing of the 14-nm FinFET device is only about 35 nm, and the critical charge decreases to sub-fC, the introduction of the FinFET structure leads to the change of charge collection and the sensitive volume sharing mechanism , and the shallow trench isolation leads to the narrowing of the charge diffusion channel. On the other hand, the surface area of the sensitive volume decreases to 0.0024 μm<sup>2</sup>, resulting in a significant decrease in the soft error rate of both SBU and MCU in the 14-nm process.

A Lightweight Network Deployed on ARM Devices for Hand Gesture Recognition

Hand gestures are a well-known and straightforward method of human-computer interaction. The majority of the study focused on hand gesture recognition. However, little work has been done to develop a complete set of gesture recognition applications. With the improvement of model feature extraction ability and the increase in the number of model parameters, it is becoming more challenging to achieve a small memory footprint on mobile devices based on an ARM architecture or CPU devices based on x86 architecture. However, these existing methods are heavy, requiring more memory and inference time. The execution of memory-efficient CNNs without compromising accuracy has been a challenge, especially when the inference has to be performed on an edge computing device in real time. Therefore, we propose a lightweight network for hand gesture recognition (LHGR-Net) and deploy it on a Raspberry Pi. LHGR-Net consists of three main parts: the base network structure, the multiscale structure (MSS), and the lightweight attention structure (LAS). We present pre-trained weights that are learned from other data to initialize the network structure. In addition, the LHGR-Net model was made to be deployed on a Raspberry Pi, and a deployed model can be used to control home appliances. Extensive experiments show that our method achieves almost as good as state-of-the-art performance in hand gesture recognition and running time.

Система персонального поиска людей при пожарах и чрезвычайных ситуациях

PURPOSE. The article deals with the issues of justifying possibility for using personal mobile device to search for people by Wi-Fi signal emission power. In case of fire individuals from technical staff at the facility under protection may not notice or hear the warning about fire and evacuation start. Having lost time to evacuate people may be cut off from main escape routes and become fire hazardous factors’ victims. METHODS. Using statistical model (ITU-R 1238) for calculations inside buildings and premises and data on routers location and placement order, an experiment has been conducted to locate a person when his mobile phone emits only residual signal power at this person’s specific location. FINDINGS. To simulate search for people and calculate matrix of signal power loss indoors and matrix of signal power levels at receiver input MatLab R2018 system has been used. Using two-way radio channel (based on Wi-Fi wireless network) is mandatory for system functioning to search for people in buildings, which allows not only identifying a person but also determining his exact location. It should be taken into account that dividing the room into cubes with dimensions 0.5×0.5×0.5 m makes it possible to determine person’s position in a particular place – lying or standing. RESEARCH APPLICATION FIELD. It is advisable to include study results in research and development work of EMERCOM of Russia research organizations and other ministries and departments involved in fire safety systems creation for critical protected facilities. CONCLUSIONS. Using the system for personal search during fires and emergencies will make it possible to locate people carrying mobile devices in real time and evacuate them to a safe zone when required.

Застосування мікроконтролера Rasрberry Pi для управління та моніторингу ІоТ систем

The article considers the issue of using the Rasberry Pi microcontroller to manage and monitor IoT elements. It is shown that currently there is a sufficiently large number of objects on the market that can be automated and many companies that offer different options to meet the needs of the client. There is also a worldwide demand for automation and remote control of various objects. Moreover, the need for automation can arise not only at enterprises with multi-thousand budgets, but also at ordinary consumers who need to be offered alternative developments that would be much cheaper and easier to operate. After a while, IoT-based technologies will be widely used in almost all production enterprises. The creation of control and monitoring systems for Internet of Things elements is a topical issue, as a large number of devices capable of exchanging data without human intervention are appearing, both in everyday life and in industry. Therefore, the purpose of this article is to research means for building IoT and to determine methods of managing and monitoring IoT elements using the example of using a Rasberry Pi microcontroller The article analyzes the components of the IoT system and proposes a monitoring and control system for its components based on the Raspberry Pi microcontroller. Such a system can monitor the state of the sensors via the Internet, when information updates on the web server are read according to the developed algorithm provided in the Raspberry Pi, and then the system responds to certain instructions with a high degree of information protection. The user can directly log in and interact with the embedded device in real time. Using the Pasbperry Pi microcontroller allows you to provide all the requirements for building a control and monitoring system for IoT elements and is an affordable technical solution that can be used in almost all industries and home use. The proposed system is energy efficient, intelligent, low cost, portable and high performance.

An approach for real time management of global manufacturing enterprises based on Digital Data Stream

Advances in sensor technology, IOTs, communication technologies, computing, data management and analytics is changing the way modern global manufacturing enterprises are managed. With appropriate design and architecture of these technologies it is possible to use digital data streams to manage these enterprises in real time. This paper focuses on issues related to the design of these systems. Specifically, we focus on developing approaches for the design of autonomous services that receive data from local devices (e.g. sensors) in real time, do some processing in real time, communicate with other services, and respond to stimuli received from other services in real time. This allows localization of appropriate decision making. These services pass on relevant information to other related services in a web like architecture.

Ultra-fast, sensitive and low-cost real-time PCR system for nucleic acid detection.

Nucleic acid detection directly identifies the presence of pathogenic microorganisms and has various advantages, such as high sensitivity, commendable specificity and a short window period, and has been widely used in many fields, such as early tumor screening, prenatal diagnosis and infectious disease detection. Real-time PCR (polymerase chain reaction) is the most commonly used method for nucleic acid detection in clinical practice, but it always takes about 1-3 hours, severely limiting its application in particular scenarios such as emergency testing, large-scale testing and on-site testing. To solve the time-consuming problem, a real-time PCR system based on multiple temperature zones was proposed, which realized the speed of temperature change of biological reagents from 2-4 °C s-1 to 13.33 °C s-1. The system integrates the advantages of fixed microchamber-type and microchannel-type amplification systems, including a microfluidic chip capable of fast heat transfer and a real-time PCR device with a temperature control strategy based on the temperature difference. The detection of HCMV biological samples using the real-time PCR system in this research took only 15 min, which was 75% shorter compared to the commercial qPCR instrument such as BIO-RAD, and the detection sensitivity remained essentially the same. The system could complete nucleic acid detection within 9 min under extreme conditions, characterized by fast detection speed and high sensitivity, providing a promising solution for ultra-fast nucleic acid detection.

Energy-Efficient Routing Protocol with Multi-Hop Fuzzy Logic for Wireless Networks

A Wireless Sensor Network (WSN) becomes a newer type of real-time embedded device that can be utilized for a wide range of applications that make regular networking which appears impracticable. Concerning the energy production of the nodes, WSN has major issues that may influence the stability of the system. As a result, constructing WSN requires devising protocols and standards that make the most use of constrained capacity, especially the energy resources. WSN faces some issues with increased power utilization and an on going development due to the uneven energy usage between the nodes. Clustering has proven to be a more effective strategy in this series. In the proposed work, a hybrid method is used for reducing the energy consumption among CHs. A Fuzzy Logic-based clustering protocol FLUC (unequally clustered) and Fuzzy Clustering with Energy-Efficient Routing Protocol (FCERP) are used. A Fuzzy Clustering with Energy Efficient Routing Protocol (FCERP) reduces the WSN power usage and increases the lifespan of the network. FCERP has created a novel cluster-based fuzzy routing mechanism that uses a limit value to combine the clustering and multi-hop routing capabilities. The technique creates uneven groups by using fuzzy logic with a competitive range to choose the Cluster Head (CH). The input variables include the distance of the nodes from the ground station, concentrations, and remaining energy. The proposed FLUC-FCERP reduces the power usage and improves the lifetime of the network compared with the existing algorithms.

Development of algorithm for work intensity evaluation using excess overwork index of construction workers with real-time heart rate measurement device.

The construction workers are vulnerable to fatigue due to high physical workload. This study aimed to investigate the relationship between overwork and heart rate in construction workers and propose a scheme to prevent overwork in advance. We measured the heart rates of construction workers at a construction site of a residential and commercial complex in Seoul from August to October 2021 and develop an index that monitors overwork in real-time. A total of 66 Korean workers participated in the study, wearing real-time heart rate monitoring equipment. The relative heart rate (RHR) was calculated using the minimum and maximum heart rates, and the maximum acceptable working time (MAWT) was estimated using RHR to calculate the workload. The overwork index (OI) was defined as the cumulative workload evaluated with the MAWT. An appropriate scenario line (PSL) was set as an index that can be compared to the OI to evaluate the degree of overwork in real-time. The excess overwork index (EOI) was evaluated in real-time during work performance using the difference between the OI and the PSL. The EOI value was used to perform receiver operating characteristic (ROC) curve analysis to find the optimal cut-off value for classification of overwork state. Of the 60 participants analyzed, 28 (46.7%) were classified as the overwork group based on their RHR. ROC curve analysis showed that the EOI was a good predictor of overwork, with an area under the curve of 0.824. The optimal cut-off values ranged from 21.8% to 24.0% depending on the method used to determine the cut-off point. The EOI showed promising results as a predictive tool to assess overwork in real-time using heart rate monitoring and calculation through MAWT. Further research is needed to assess physical workload accurately and determine cut-off values across industries.

一种新型自适应井下动液面实时监测装置

一种新型自适应井下动液面实时监测装置

Bilateral leg stepping coherence as a predictor of freezing of gait in patients with Parkinson's Disease walking with wearable sensors.

Fourteen participants with PD (in OFF state) were asked to walk in challenging conditions (e.g. with turning, dual-task walking, etc.) while wearing inertial motion sensors (waist, 2 shanks) and being videotaped. Occasionally, participants were asked to voluntarily stop (VOL). FOG and VOL events were identified by trained researchers based on videos. Wavelet analysis was performed on shank sagittal velocity signals and a synchronization loss threshold (SLT) was defined and compared between FOG and VOL. A proof-of-concept analysis was performed for a subset of the data to obtain preliminary classification characteristics of the novel measure. 128 FOG and 42 VOL episodes were analyzed. SLT occurred earlier for FOG (MED=1.81 sec prior to stop, IQR=1.57) than for VOL events (MED=0.22 sec, IQR=0.76) (Z=-4.3, p<0.001, ES=1.15). These time differences were not related with measures of disease severity. Preliminary results demonstrate sensitivity of 98%, specificity of 42% (mostly due to 'turns' detection) and balanced accuracy of 70% for SLT-based prediction, with good differentiation between FOG and VOL. Wavelet analysis provides a relatively simple, promising approach for prediction of FOG in people with PD.