Remote Monitoring Center Research Articles

Acute remote home monitoring of acutely ill patients with COVID-19: how Dutch home monitoring initiatives were organized during the pandemic

BackgroundAcute remote home monitoring of acutely ill patients with COVID-19 holds potential for early detection of deterioration and thus subsequentearly intervention that may prevent or mitigate progression to severe illness and need for respiratory support. Our aim was to describe common features of acute remote home monitoring programs for acutely ill patients with COVID-19 in the Netherlands.MethodsWe performed literature searches (both grey and academic) between 1st March 2020 and 1st March 2023 to identify Dutch acute remote home monitoring initiatives, excluding studies on early hospital discharge. From the available protocols, we extracted relevant information on patient eligibility, organization of acute remote home monitoring and home management.ResultsWe identified and approached ten acute remote home monitoring initiatives for information regarding their used protocols. Seven out of ten protocols were retrieved and assessed. All initiatives focused on adult patients with COVID-19 who where at risk of developing severe COVID-19, and all initiatives provided close follow-up through remote home monitoring using medically certified pulse oximeters. Daily measurements included peripheral oxygen saturation (all initiatives, n = 7), body temperature (n = 6), heart frequency per minute (n = 4) and breathing rate per minute (n = 4). For follow-up and review of measured values, in most initiatives (n = 6) the physician (general practitioner or hospital physician) in charge was supported by a dedicated monitoring center. In 5 out of 7 initiatives, the general practitioner (GP) was responsible for supervising the patients and monitoring staff.ConclusionThe acute remote home monitoring initiatives that emerged in the Netherlands during the first wave of the COVID-19 pandemic were similarly organized. Common building blocks for home monitoring include daily check of peripheral oxygen saturation, monitoring through a dedicated remote monitoring center alongside healthcare personnel and a supervising physician.

Creation of Remote Monitoring Centers for Patients with Spinal Cord Injury Based on the Principles of Value-Oriented Rehabilitation Model: Relevance and Organization Principles

Due to the widespread introduction into the practice of Russian healthcare of the International Classification of Functioning, Disability and Health (ICF), the development of digital medicine requires the reorganization of rehabilitation care in the Russian healthcare system. Special attention is paid to the models of 5P medicine and trinitarianism. In this regard, it seems relevant to form the basic principles of building a remote monitoring center model for patients with spinal cord injury. To this end, the authors conducted a search for publications in the PubMed databases, e-Library (the rubricator of clinical recommendations and regulatory legal acts), as well as additional sources in the reference lists. As a result, 86 publications and literature sources were identified, analyzed and systematized, 25 of which are included in this review. The following research methods were used: analytical method, data copying, SWOT analysis. As a result, from the perspective of a value-oriented model of rehabilitation, 5P medicine, and trinitarianism, the need for creating regional remote monitoring centers for patients with spinal cord injury to provide them with the necessary assistance, as well as other patients traveling in wheelchairs, was justified. The principles are substantiated, as well as the possibilities and threats of the formation of regional remote monitoring centers are shown. In conclusion, it is emphasized that the creation of such centers for remote monitoring of low-mobility patients based on ICF in Russia will contribute to optimizing resources, optimal routing and accessibility of medical rehabilitation care.

Abstract 819: Feasibility of patient-centered home care (PCHC) to reduce disparities in high-risk black men with advanced prostate cancer

Abstract The objective of our study is to evaluate the feasibility, acceptance, and impact of patient-centered home care (PCHC) on patient reported outcomes (PROs) and health-related quality of life (HQoL) of black men with advanced prostate cancer (CaP). Meeting patients where they are and offering treatment in or closer to their homes reduce psychological distress and increase treatment compliance, especially for disadvantaged patients in rural areas, those on low incomes, with poor access to transport, elderly and people with disabilities. In 2023, Mayo Clinic has developed the Cancer Care Beyond Walls (CCBW) program, a cancer care delivery model that integrates virtual with in facility treatment and provides a package of care to support administration of cancer-directed therapy (chemotherapy, immunotherapy, hormonal therapy) and/or supportive care in the patients’ homes. Our study will assess if patients and families are comfortable with cancer therapy at home, what factors influences their decision, and use this data to inform our understanding of the proportion of the black men with advanced CaP who would be willing to receive and would benefit from this level of care at home. Patients with advanced CaP from our practice requiring active anti-cancer therapy are administered a brief questionnaire regarding preference for location of therapy at the infusion center or in the home, with perceived difficulties and advantages of each approach. A focus group session with prostate cancer survivor advocates is also conducted to capture patients’ thoughts, feelings, attitudes, and questions towards cancer treatments being administered at home versus a hospital setting. In addition, we are conducting an observational study of 20 patients with advanced prostate cancer receiving supportive care/symptom management and/or anti-cancer therapy in the home as part of the Mayo Clinic CCBW Program to assess the safety of cancer directed therapy when administered at home by a home health provider with remote patient monitoring and command center support, and establish the impact of home cancer treatment administration on patient-reported function and global health/quality of life, patient-reported symptoms, clinical outcomes, and cost of care. Successful completion of the project will deliver data on patient understanding and acceptability of cancer care at home, strategies for overcoming barriers to care for underserved communities, and the foundation from which we discover, translate and apply new knowledge in administering personalized care to vulnerable populations. Citation Format: Roxana S. Dronca, Folakemi Odedina, Che Ngufor, Kimlin Ashing, Ernest Kaninjing, Solomon Rotimi. Feasibility of patient-centered home care (PCHC) to reduce disparities in high-risk black men with advanced prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 819.

Artificial intelligence based abnormal detection system and method for wind power equipment

The existing traditional monitoring methods are not ideal for identifying abnormal states in remote real-time monitoring of power system equipment due to adverse weather conditions such as haze and snow. The traditional monitoring methods for wind power equipment mainly rely on manual inspections and regular maintenance, which have problems such as high labor costs, low monitoring efficiency, and low monitoring accuracy. In order to improve the effectiveness of anomaly recognition for power system equipment, this paper proposes a remote real-time monitoring anomaly recognition method for power system equipment based on artificial intelligence technology. Firstly, this article uses pan tilt cameras to capture real-time images of power system equipment and transmit them to a remote monitoring center. The remote monitoring center captures real-time images of the equipment in the video stream and performs real-time image preprocessing. Then, the variational mode decomposition method is used to extract the abnormal state features of power system equipment in the image, and this feature is input into the support vector machine as a training sample to achieve real-time recognition of abnormal state of power system equipment. This article was also conducting fault diagnosis for four sets of wind turbines in the experimental section. According to the experimental results, it can be concluded that the rotational speed of wind turbine 1 increased from around 12 rpm to around 30 rpm during the day. During the day, the temperature of wind turbine 2 increased from around 25 °C to around 40 °C, while wind turbine 3 remained in a stopped state and the current speed decreased to 0. Wind turbine 4 also decreased from around 10 rpm to 0 during the day. From this, it can be concluded that the wind power equipment anomaly detection system based on artificial intelligence can clearly determine the abnormal situation of wind turbines. The wind power equipment anomaly detection system based on artificial intelligence can timely and accurately identify the abnormal situation of WPE, and can provide a new wind power equipment anomaly detection method based on artificial intelligence for the wind power industry. This can provide more accurate and reliable support for the operation and maintenance of wind power equipment, and also provide practice and exploration for the application of artificial intelligence in the industrial field.

Transformation of Eye Care Through Innovations.

Transformation of Eye Care Through Innovations.

Developing a firewater deluge monitoring and forecasting system based on GA-ARMA model

PurposeThe firewater deluge system (FDS) can provide water automatically through a deluge valve when a fire breaks out. However, there are many fire hazards caused by the abnormal operating state of the FDS. To monitor and predict the working state of the FDS, this paper aims to propose a firewater deluge monitoring and forecasting system using the Internet of Things (IoT) technology.Design/methodology/approachThe firewater deluge monitoring and forecasting system consists of three layers: the sensing layer, network layer and application layer. The firewater pressure obtained by the monitoring nodes was transmitted to the local gateway and then to the remote monitoring center. In the application layer, an autoregressive moving average (ARMA) model was put forward to forecast the firewater pressure. Furthermore, a genetic algorithm (GA) was proposed to perfect the order determination method of the ARMA model. Finally, a Web application was developed to display the real time and predicted working status of the FDS.FindingsThe predicted results show that the ARMA model improved by the GA (GA-ARMA) is significantly better than traditional ARMA models in terms of mean relative error, mean absolute error and mean square error. Moreover, the proposed system is demonstrated to be effective, and an early warning can be alerted to remind users of repairing abnormal FDS equipment ahead of fire dangers.Originality/valueThe proposed system cannot only be applied to the FDS of all buildings to avoid fire hazards by monitoring and predicting the working state of the FDS, but can also be widely used in other fields, such as environmental monitoring, intelligent logistics and intelligent transportation.

A Low-Cost Online Data Acquisition and Processing System for Industrial Pollutants’ Monitoring

Recently, the prevention and control of industrial pollution has attracted extensive attention. Many studies based on emission data have achieved great success, but there are relatively few studies on the emission data acquisition. To this end, we propose a data acquisition and processing system (DAPS) for online monitoring of industrial pollutants. The system receives real-time emission data through the RS485, automatically generates periodic data, and saves it in the SQL Server database. Real-time Ethernet (RTE) is used to transmit control signals between the system and programmable logic controllers (PLCs). Emission data is transmitted to local industrial control systems and remote monitoring centers (RMCs) via a wireless network. We tested the acquisition function and communication function of the system through experiments and evaluated the overall performance of the system by observing the memory and CPU usage. The system is characterized by simple implementation and versatility and can be applied to continuous monitoring of various industrial pollutants.

Multi index evaluation method of pathological weight loss effect of aerobic exercise based on telemedicine monitoring

INTRODUCTION: Pathological obesity seriously endangers human health. OBJECTIVES: A multi index evaluation method of pathological weight loss effect of aerobic exercise based on telemedicine monitoring is proposed to evaluate the pathological weight loss effect of aerobic exercise by using telemedicine monitoring system. METHODS: According to the indexes of aerobic exercise affecting weight loss effect, a multi index evaluation system of pathological weight loss effect of aerobic exercise was established. The medical sensor of the telemedicine monitoring system is used to collect the index data in the multi index evaluation system of pathological obese personnel. The medical sensor uses the wireless node to transmit the collected data to the remote monitoring center. The evaluation module of the remote monitoring center uses the collected data and selects the fuzzy comprehensive evaluation method to evaluate the pathological weight loss effect of aerobic exercise. RESULTS: The experimental results show that this method can effectively use the telemedicine monitoring system to collect the physiological parameters of pathological obese people, and use the parameter collection results to evaluate the effect of aerobic exercise on pathological weight loss. CONCLUSION: The proposed methods can provide basis for human aerobic exercise pathological weight loss.

A Novel BeiDou Satellite Transmission Framework With Missing Package Imputation Applied to Smart Ships

Obtaining voyage data through a vessel monitoring system (VMS) and transmitting it to a remote monitoring center through satellites is an important link to realize the information perception of smart ships. However, improving data quality to ensure the integrity of information is still an open question. Taking into account the complex and harsh marine environment, a BeiDou satellite transmission link will inevitably suffer the challenge of packet loss. Therefore, this paper proposes a novel BeiDou satellite transmission framework with missing package imputation to improve the information perception ability of smart ships. In particular, we propose a two-stage missing packet imputation strategy (T-MPI). First, a bidirectional recurrent neural network (Bi-RNN) based on temporal view imputation is designed to learn the time correlation of the data. Second, considering the attributive view imputation of multivariate data, an autoencoder with a linear aggregation module (LA-AE) is proposed to capture sudden changes in the ship’s complex sailing state. An experimental platform was established to verify the developed framework, and real freighter transportation data were used to prove the effectiveness of our proposed imputation strategy under complex sailing conditions.

Organization of the center for remote monitoring of implantable cardiac devices

Remote monitoring of implantable devices is a solution allowing optimization of treatment in response to changes in the physiological parameters obtained by various sensors locates within the patients’ cardiovascular system. The technical efficiency of transmitting information at a distance, however, does not ensure the complete functionality of the system. The goals of care, i.e. preventing the negative consequences of arrhythmic events, prevention of exacerbation of heart failure, early detection of dysfunction of therapeutic systems, and many others, can only be achieved with the proper response of the staff of remote monitoring center. Organization of the remote monitoring center, the work culture should be based on three elements: competent and educated personnel updating their knowledge correct identification and education of patients – program participants transparent and reliable information flow The effective implementation of these three elements enables safe for patients and employees providing care using the latest technology in the field of electrotherapy.

Monitoring system based on wireless temperature measuring device

This paper analyzes the current common problems in substation temperature measurement, and the transformer temperature measurement system is designed. The system includes a temperature collection node, a temperature concentrator and a remote monitoring center, which can perfectly realize the functions of temperature collection, wireless transmission and online monitoring. Through the actual application of the software, it can be seen that the various modules are operating normally and have reached the design goals.

Sustainable solar powered battery-free wireless sensing for food cold chain management

Green, sustainable and non-stop wireless sensing is not only one of the critical issues in the widespread applications of wireless sensing to guarantee the food quality and safety in cold chain, but also one of the important ways to improve the sustainability of the food cold chain. The aim of this paper is to propose and develop a sustainable solar powered battery-free sensing system for food cold chain management. The system includes the sustainable solar energy harvesting layer, battery-free wireless sensing layer and remote monitoring and management center. The sustainable solar power performance, battery-free wireless sensing performance, energy consumption performance, emergy based sustainability performance and the system evaluation performance of the sustainable solar powered battery-free wireless sensing system were analyzed and evaluated. The proposed and developed sustainable solar powered battery-free sensing system could reduce the average energy consumption by 87.04%, the cost by 15.3% and increase the greening, sustainability and non-stop monitoring of the food cold chain by comparing with the battery powered wireless sensing system. This study could also provide some theoretical and experimental methods for the other food non-stop monitoring in cold chain to improve the sustainable development and ensure the food quality and safety. It is also possible to integrate more different sensors for non-stop cold chain battery-free wireless sensing.

Design of Intelligent Drip Infusion Control System Based on Huawei Internet of Things Platform

In order to solve the problems of heavy labor burden, cumbersome work, patients can not get comfortable care and low medical efficiency, an intelligent drip infusion control system based on Huawei Internet of things platform is designed. The system first describes the system implementation technical principle, hardware design idea, Huawei cloud platform upper management application solution idea, using NB-IoT to communicate with Huawei cloud platform, Huawei cloud server design, web back-end, web front-end and mobile app design process. The test results show that the system has the functions of web page and mobile app remote centralized monitoring, remote speed regulation and remote run out alarm, which reduces the burden of nurses, reduces the contact time between nurses and patients, and improves the medical efficiency.

A Q-Learning Approach for Real-Time NOMA Scheduling of Medical Data in UAV-Aided WBANs

Unmanned Aerial Vehicles (UAVs) have emerged as a flexible and cost-effective solution for remote monitoring of the vital signs of patients in large-scale Internet of Medical Things (IoMT) Wireless Body Area Networks (WBANs). This paper deals with the problem of using UAVs for real-time scheduling of the transmission of vital signs in delay-sensitive IoMT WBANs. The main challenge for such a network is to timely and reliably transmit the vital signs of patients to the remote monitoring center without interrupting their daily lifestyles. To achieve this goal, we propose a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> -learning-based algorithm to optimize the trajectory of each UAV, as the mobile Base Station (BS), to harvest vital signs of patients in outdoor applications, especially in unreachable areas. In this algorithm, UAVs learn to reach the best 3D position by discovering the network environment step-by-step. It stands for the position in which the covered patients by each UAV have the highest transmission rate, the least delay and energy consumption. Moreover, we employ the Non-Orthogonal Multiple Access (NOMA) technique to simultaneously schedule multiple transmissions by accepting a degree of interference between them in order to enhance the spectrum efficiency of the network. Eventually, the performance of our proposed scheme is evaluated via extensive simulations in terms of throughput, energy consumption, and delay. The simulation results show that our proposed scheme iteratively converges to the benchmark value of the mentioned factors by increasing the information of cluster environment through episodes.

Remote Monitoring Programs for Cardiac Conditions

&#x0D; Remote monitoring is a type of telehealth whereby health care is delivered to patients outside traditional settings by allowing health data to be exchanged between patients and health care providers using telecommunication techniques (e.g., video conferencing) or stand-alone devices (e.g., portable heart rate monitors). The goals of remote monitoring centre around promoting home-based self-management to improve patient outcomes and/or reduce health system usage.&#x0D; CADTH’s Health Technology Assessment included the following analyses:&#x0D; &#x0D; A Realist Review: This sought to identify key perceived or actual mechanisms of remote monitoring programs. Substantial evidence was available regarding the use of remote monitoring programs for heart failure (n = 64) and cardiac rehabilitation (n = 23), limited evidence was available for atrial fibrillation (n = 4), and none was available for hypertension.&#x0D; A Perspectives and Experiences Review: This thematic synthesis of primary qualitative research sought to understand and describe peoples’ experiences with and perspectives on remote monitoring programs for cardiac conditions. CADTH also engaged patients and caregivers directly in a patient engagement section.&#x0D; An Ethics Review: This sought to identify and reflect upon key ethical issues that should be considered when contemplating the implementation of remote monitoring programs.&#x0D; &#x0D; &#x0D; Overall, the vast majority of sampled patients, caregivers, and health professionals consistently found or perceived remote monitoring programs across different cardiac conditions to be easy to use and beneficial to health.&#x0D; Remote monitoring programs may be an attractive adjunct as opposed to an alternative to existing health professionals and services.&#x0D; Although remote monitoring programs may ultimately reduce avoidable hospitalizations, they may increase net costs and workload during set-up and operational phases without careful pathway design and expectations management.&#x0D; More research is needed to identify the costs and cost-effectiveness of remote monitoring programs across chronic cardiac conditions.&#x0D;

Data Collection of Digital Monitoring System for Agricultural Facilities Environment

In order to realize the intelligent control of the agricultural facility greenhouse environment cluster, the paper designs and implements an agricultural facility greenhouse environment cluster monitoring system based on RS485 bus and Modbus protocol. The system consists of on-site data acquisition and control part, remote monitoring centre monitoring software part and communication protocol part. We use the RS485 bus with Modbus protocol to realize the communication between the monitoring centre host and the microcontrollers of each greenhouse. The paper uses the BP neural network PID control algorithm to achieve the intelligent control of the agricultural greenhouse environment. Use Qt software to design a human-computer interaction interface to realize remote control of the greenhouse cluster. The experimental results show that the system can correctly collect the temperature, humidity and light intensity of the agricultural greenhouse environment, and can effectively control the environmental parameters of each greenhouse through the action of the control relay.

STUDY OF THE ECONOMIC EFFICIENCY OF PROJECTS FOR DIGITAL TRANSFORMATION OF THE BP MONITORING MODEL

Objective: To investigate the economic efficiency of business models for a project for BP monitoring in patients with hypertension in the context of digital transformation of medical services. Design and method: Applied functional, structural and business modeling of design options, methods for assessing market capacity, competition analysis, financial modeling, project sensitivity analysis, analysis of regulatory constraints. Results: We studied two business models - implemented in commercial medicine and in a budgetary healthcare institution. Common in the models is the patient service scheme (supplying it with a certified tonometer with a built-in GSM or Bluetooth module - measuring BP - transmitting encrypted data to the remote monitoring center - storing it in a cloud database and the patient's electronic medical record - monitoring BP indicators - doctor's response to critical deviations in measurement results — patient feedback through the messenger). The difference in models is related to the sources and form of payment. In a private clinic, it is possible to use the patient's personal funds, voluntary medical insurance schemes, compulsory medical insurance (CMI), in a budgetary healthcare institution - payment at the CMI rate. The considered options turned out to be cost-effective (NPV &gt; 0) with a discounted payback period from 2.8 (option 1) to 3.35 years (option 2). In case of state insurance system, the time for launching a project is lengthened due to the agreeing period on the telemonitoring tariff; the methods of stimulating the medical personnel participating in the RMBP are different. The sensitivity analysis showed that the most critical factor is the tariff level for the service (the acceptable range is 4.84 -8.81 euros for the telemedicine component), investments vary in the range from 225988.7 to 293785.3 euros. IRR of the project - 38% -45%, PI - 1.6 -1.75. Conclusions: The use of telemedicine technologies is economically feasible in both commercial and budgetary institutions. An increase in the project's efficiency indicators is possible due to the coverage of large regions. The accumulation and analysis of big data as a result of monitoring will create conditions for the chronopharmacology of antihypertensive drugs.

COVID-19 community care in Israel-a nationwide cohort study from a large health maintenance organization.

BackgroundAmong the many medical challenges presented by the COVID-19 pandemic, management of the majority of patients in community outpatient settings is crucial. The aim of this study was to describe the characteristics and outcomes among confirmed COVID-19 cases who were managed at three settings: two outpatient settings and one inpatient.MethodsA retrospective database cohort study was conducted in a large Israeli Health Maintenance Organization. All COVID-19 cases diagnosed between 28 February 2020 and 20 July 2020 were included. Cases in the community settings were managed through a nationwide remote monitoring center, using preliminary telehealth triage and 24/7 virtual care. Outcome parameters included hospital admission, disease severity, need for respiratory support and mortality.ResultsAbout 5448 cases, aged range 0–97 years, were enrolled; 88.7% were initially managed as outpatient either at home or in designated hotels, 3.1 and 2.1% of them, respectively, later required hospitalization. The main reason for hospitalization was dyspnea; 12 were diagnosed with severe disease; 56 patients (1.3%) died, five (0.1%) of whom were initially allocated to the outpatient settings.ConclusionsCare for appropriately selected COVID-19 patients in the community provides a safe and effective option. This can contribute to reducing the hospitalization burden, with no evidence of increased morbidity or mortality.

Retracted] Physiological Index Monitoring of Wearable Sports Training Based on a Wireless Sensor Network

According to the development needs of wireless sensor networks, this paper uses the combination of embedded system and wireless sensor network technology to design a network node platform. This platform is equipped with a sports training sensor module to measure the physiological indicators of the ward in real time. The network node sends the collected physiological parameters to a remote monitoring center in real time. First, according to the generation mechanism of the physiological index signal and the characteristics of the physiological index signal, the wireless sensor network analysis and processing method are used to denoise the physiological index signal, and the wireless sensor network package is used to extract the characteristics of the physiological index, indicating different types of respiration. The energy characteristics of the sound physiological index signals are different, which verifies the feasibility of the independent component analysis method for separating the physiological index and the physiological index signal of the heart sound. Secondly, the hardware system of physiological index signal acquisition is designed, and the selection principle of the hardware unit is introduced. At the same time, the system structure of the monitor is designed, and then, the wireless sensor network sensor node is researched, the hardware of the wearable monitor system is designed, and the hardware architecture and working mode based on the single‐chip MSP430F149 are given. Finally, the wireless hardware platform includes the following main modules: sensor part, preprocessing circuit module, microprocessing module based on MSP430 low power consumption, wireless transceiver module based on RF chip CC2420, and power supply unit used to provide energy.

Design of Self-Healing Control Method for Photo Voltaic Distribution Network of Internet of Things

During the construction of photo voltaic grid-connected distribution network, the self-healing control system is generally composed of monitoring computer, communication cable, communication interface, photoelectric converter, bus connector and multi-film optical cable. The remote centralized monitoring is realized by communicating with the local controller of the unit. Its network mode model for industrial Ethernet, communication system and implementation of the need for large-scale but photo voltaic (pv) grid power distribution network with single purpose of large number, wide distribution of the region, and the communication of capital concentration is much higher than power generation capacity of thermal power, hydro power, nuclear power or if based on Internet technology and network, not only can reduce the communication equipment of the implementation of the capital, can also provide follow-up self-healing control rising space.