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Background: Patients with heart failure have high rehospitalisation rates and poor cardiovascular outcomes. Home-based monitoring (HBM) has emerged with promising results in different settings. However, its long-term effects on patients recently admitted for acute decompensated heart failure (ADHF) remain uncertain. Methods: We systematically searched PubMed, Embase, and Cochrane Library for randomised controlled trials (RCTs) comparing HBM with usual care (UC) that were published between database inception and June 24, 2023. We included studies with patients admitted for ADHF in the previous 6 months and with a minimum follow-up of 6 months. We excluded studies with patients hospitalised for reasons other than ADHF and studies with disproportional education interventions between arms. Statistical analyses were performed using R software version 4.3.2. We pooled risk ratios (RR) and mean differences (MD) with 95% confidence intervals (CI) for categorical and continuous outcomes, respectively. Cochrane Collaboration's tool for assessing risk of bias in RCTs (RoB 2) was used to assess study quality. Publication bias was assessed via funnel plots and Egger's test, and heterogeneity was assessed through I2 statistics and sensitivity analysis. The protocol for this systematic review and meta-analysis was registered in the International Prospective Register of Systematic Reviews (PROSPERO, CRD42023465359). Findings: We included 16 RCTs comprising 4629 patients, of whom 2393 (51.7%) were randomised to HBM and 3150 (68%) were men. Follow-up ranged from six to fifteen months. As compared with UC, HBM significantly reduced all-cause mortality (RR 0.75; 95% CI 0.61, 0.91; p = 0.005), all-cause hospitalisations (RR 0.82; 95% CI 0.70, 0.97; p = 0.018), cardiovascular (CV) mortality (RR 0.53; 95% CI 0.36, 0.79; p = 0.002), hospitalisations for heart failure (RR 0.75; 95% CI 0.62, 0.91; p = 0.004), and CV hospitalisations (RR 0.72; 95% CI 0.55, 0.95; p = 0.018). There were no significant differences in length of hospital stay (MD 0.97 days; 95% CI -0.90, 2.84; p = 0.308). Interpretation: In patients recently admitted with ADHF, HBM significantly reduces long-term all-cause mortality and hospitalisations, CV mortality and hospitalisations, and hospitalisations for heart failure, as compared with UC. This supports the implementation of HBM as a standard practice to optimise patient outcomes following admissions for ADHF. However, future studies are warranted to evaluate the efficacy and safety of implementing HBM in the real-world setting. Funding: None.

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BACKGROUND: Flash glucose monitoring systems like the FreeStyle Libre (FSL) sensor have gained popularity for monitoring glucose levels in people with diabetes mellitus. This sensor can be paired with an off-label converted real-time continuous glucose monitor (c-rtCGM) plus an ad hoc computer/smartphone interface for remote real-time monitoring of diabetic subjects, allowing for trend analysis and alarm generation. OBJECTIVES: This work evaluates the accuracy and agreement between the FSL sensor and the developed c-rtCGM system. As real-time monitoring is the main feature, the system's connectivity was assessed at 5-min intervals during the trials. METHODS: One week of glucose data were collected from 16 type 1 diabetic rats using the FSL sensor and the c-rtCGM. Baseline blood samples were taken the first day before inducing type 1 diabetes with streptozotocin. Once confirmed diabetic rats, FSL and c-rtCGM, were implanted, and to improve data matching between the two monitoring devices, the c-rtCGM was calibrated to the FSL glucometer readings. A factorial design 2 × 3^3 and a second-order regression was used to find the base values of the linear model transformation of the raw data obtained from the sensor. Accuracy, agreement, and connectivity were assessed by median absolute relative difference (Median ARD), range averaging times, Parkes consensus error grid analysis (EGA), and Bland-Altman analysis with a non-parametric approach. RESULTS: Compared to the FSL sensor, the c-rtCGM had an overall Median ARD of 6.58%, with 93.06% of results in zone A when calibration was not carried out. When calibration frequency changed from every 50 h to 1 h, the overall Median ARD improved from 6.68% to 2.41%, respectively. The connectivity evaluation showed that 95% of data was successfully received every 5 min by the computer interface. CONCLUSIONS AND CLINICAL IMPORTANCE: The results demonstrate the feasibility and reliability of real-time and remote subjects with diabetes monitoring using the developed c-rtCGM system. Performing calibrations relative to the FSL readings increases the accuracy of the data displayed at the interface.

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Today, maintaining an Internet connection is indispensable; as an example, we can refer to IoT applications that can be found in fields such as environmental monitoring, smart manufacturing, healthcare, smart buildings, smart homes, transportation, energy, and others. The critical elements in IoT applications are both the Wireless Sensor Nodes (WSn) and the Wireless Sensor Networks. It is essential to state that designing an application demands a particular design of a WSn, which represents an important time consumption during the process. In line with this observation, our work describes the development of a modular WSn (MWSn) built with digital processing, wireless communication, and power supply subsystems. Then, we reduce the WSn-implementing process into the design of its modular sensing subsystem. This would allow the development and launching processes of IoT applications across different fields to become faster and easier. Our proposal presents a versatile communication between the sensing modules and the MWSn using one- or two-wired communication protocols, such as I2C. To validate the efficiency and versatility of our proposal, we present two IoT-based remote monitoring applications.

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ABSTRACT Home hemodialysis (HD) and automated peritoneal dialysis (APD) have advantages over HD in hospitals or HD centers. Home therapies are generally less expensive and give patients greater mobility and freedom for work, school, family, and recreational activities. Technological advances have made it possible to complement APD with devices for remote monitoring (RM) of the patient. With them, objective information generated in the APD device is collected and sent to repositories "in the cloud" for analysis or at the time decided by the health team. With APD+RM, it is possible to monitor therapeutic compliance, effective dialysis time, ultrafiltration volumes, inflow and outflow patterns of dialysis fluid, and patient actions to respond to alarms that indicate deviations from the parameters set by the nephrologist. The results of APD+RM show good acceptance by the patient, nephrologists, and nurses, treatment adherence has improved, hospitalizations and technique failure have decreased, and some aspects of quality of life have improved. However, there is a lack of controlled clinical trials that reliably demonstrate lower mortality and comorbidity due to specific causes.

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Context: The technological advancement of the Internet of Things (IoT) creates opportunities in various social sectors. Patients in clinics or home care have their comfort and safety enhanced with remote monitoring, sensors and applications that control and transfer patient data. These applications must be trustworthy, since they deal with sensitive data. Purpose: The purpose of this work is to identify gaps in trustworthiness, availability, effectiveness, security and other attributes. Also, to highlight challenges and opportunities for research and give guidance on choosing the right technology or application based on the resources available to support patients and doctors, protocol of communication and maturity level of these technologies. Methodology: This work presents a systematic review of the literature following four steps: Definition of the Research Questions, Conduct Search, Screening of Papers, and Data Extraction and Mapping Process. Results: Based on the articles studied, it was possible to answer important questions about eHealth applications. The results highlight how eHealth applications can enhance patient care by monitoring health data and supporting doctors' decision-making with a reasonable level of trustworthiness. Additionally, the results demonstrate how applications can notify external caregivers in emergencies and assist in diagnosis and treatment of illnesses. However, these applications still face problems related to sensor lifetime, medical data sharing, interoperability and lack of standardization. Finally, we suggest a literature mapping to support the choice of technologies based on resources available, communication protocol and technological maturity. Conclusion: This work carries out a systematic literature review to discuss state-of-the-art eHealth applications and gather new information of current research. In this process it was possible to show how these applications work, map out their main technological characteristics to assist the decision-making process for future works and uncover eHealth applications' strengths, future perspectives and challenges, specifically related to the high level of trustworthiness necessary.

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Home hemodialysis (HD) and automated peritoneal dialysis (APD) have advantages over HD in hospitals or HD centers. Home therapies are generally less expensive and give patients greater mobility and freedom for work, school, family, and recreational activities. Technological advances have made it possible to complement APD with devices for remote monitoring (RM) of the patient. With them, objective information generated in the APD device is collected and sent to repositories "in the cloud" for analysis or at the time decided by the health team. With APD+RM, it is possible to monitor therapeutic compliance, effective dialysis time, ultrafiltration volumes, inflow and outflow patterns of dialysis fluid, and patient actions to respond to alarms that indicate deviations from the parameters set by the nephrologist. The results of APD+RM show good acceptance by the patient, nephrologists, and nurses, treatment adherence has improved, hospitalizations and technique failure have decreased, and some aspects of quality of life have improved. However, there is a lack of controlled clinical trials that reliably demonstrate lower mortality and comorbidity due to specific causes.

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BACKGROUND: With the growing use of remote monitoring technologies in the management of patients with type 2 diabetes mellitus (T2DM), caregivers are becoming important resources that can be tapped into to improve patient care. OBJECTIVE: This review aims to summarize the role of caregivers in the remote monitoring of patients with T2DM. METHODS: We performed a systematic review in MEDLINE, Embase, Scopus, PsycINFO, and Web of Science up to 2022. Studies that evaluated the role of caregivers in remote management of adult patients with T2DM were included. Outcomes such as diabetes control, adherence to medication, quality of life, frequency of home glucose monitoring, and health care use were evaluated. RESULTS: Of the 1198 identified citations, 11 articles were included. The majority of studies were conducted in North America (7/11, 64%) and South America (2/11, 18%). The main types of caregivers studied were family or friends (10/11, 91%), while the most common remote monitoring modalities evaluated were interactive voice response (5/11, 45%) and phone consultations (4/11, 36%). With regard to diabetes control, 3 of 6 studies showed improvement in diabetes-related laboratory parameters. A total of 2 studies showed improvements in patients' medication adherence rates and frequency of home glucose monitoring. Studies that evaluated patients' quality of life showed mixed evidence. In 1 study, increased hospitalization rates were noted in the intervention group. CONCLUSIONS: Caregivers may play a role in improving clinical outcomes among patients with T2DM under remote monitoring. Studies on mobile health technologies are lacking to understand their impact on Asian populations and long-term patient outcomes.

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PURPOSE OF REVIEW: Remote monitoring (RM) is the standard of care for patients with cardiac implantable electronic devices (CIEDs), particularly pacemakers. However, the long-term outcomes of RM versus conventional monitoring (CM) of pacemakers and its effectiveness in reducing in-office (IO) visits for device reprogramming require elucidation. This systematic review and meta-analysis aimed to compare the RM and CM of pacemakers over a long-term follow-up. RECENT FINDINGS: We systematically searched the PubMed/MEDLINE, Embase, Cochrane, and ClinicalTrials.gov databases for randomized controlled trials (RCTs) comparing RM and CM of pacemakers with at least 12 months of follow-up. Binary endpoints were pooled with risk ratios (RRs), whereas continuous outcomes were computed using mean differences (MDs) or standardized MDs (SMDs). Heterogeneity was assessed using I2 statistics. Among the eight included RCTs, 2159 (48.9%) of 4063 patients underwent RM. Follow-up periods ranged from 12 to 24 months. There were no significant between-group differences in all-cause mortality (RR = 1.19; 95% confidence interval [CI], 0.90-1.57; p = 0.22; I2 = 0%), stroke (RR = 0.90; 95% CI, 0.43-1.91; p = 0.79; I2 = 23%), hospitalizations for cardiovascular and/or device-related adverse events (RR = 0.95; 95% CI, 0.75-1.21; p = 0.70; I2 = 0%), and quality of life (SMD = - 0.06; 95% CI, - 0.22 to 0.10; p = 0.473; I2 = 0%). RM was associated with fewer IO visits/patient/year (MD = 0.98; 95% CI, - 1.64 to - 0.33; p = 0.08; I2 = 98%) and higher rates of atrial tachyarrhythmia (ATA) detection (RR = 1.22; 95% CI, 1.01-1.48; p = 0.04; I2 = 0%) than was CM. This meta-analysis suggests that RM of pacemakers leads to higher rates of ATA detection and fewer IO visits/patient/year, without compromising patient safety.

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BACKGROUND: Due to the health emergency of COVID-19, telemedicine has become more relevant. Remote monitoring conspicuous as a valuable tool for the clinical follow-up of kidney patients, in this case, who are treated with automated peritoneal dialysis. This study aims to describe the use of remote monitoring as a surveillance method in a cohort of patients on automated peritoneal dialysis prevent complications and COVID-19 contagion. METHODS: Study of a cohort of patients who initially participated in a randomized block clinical trial in which the use of Automated Peritoneal Dialysis with Remote Monitoring (APD-RM) was compared with conventional treatment. A descriptive analysis was performed of the rates of infection by COVID-19, the time of incidence until this, mortality, and rates of transfer to hemodialysis. In addition, survival was measured by survival curves. RESULTS: Of the 509 patients, 19 were positive for COVID-19 (incidence rate of 7.0 episodes/100 patient-year), and only six patients recovered from the infection; the death rate was 2.6 % compared to all-cause death of 9.8 %. The most affected group of patients were those over 50 years old, with 71.4 % mortality, in contrast to younger patients infected, with a mortality of 60 %. During the follow-up period, 21 patients were transferred to HD: six due to peritonitis, five due to UF failure, seven due to catheter dysfunction, one due to uremic syndrome, one due to COVID-19, and one by surgical intervention. CONCLUSION: APD-RM patients have a significant advantage over other dialysis therapies because the use of telemedicine not only provides continuity in the patient's clinical treatment but also favors the prevention of COVID-19 infection, the management and prevention of complications inherent to therapy and the preservation of the life of Peritoneal Dialysis patients.

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BACKGROUND: Patients with cardiac implantable electronic devices (CIEDs) living in rural areas have difficulty obtaining follow-up visits for device interrogation and programming in specialized healthcare facilities. OBJECTIVE: To describe the use of an assisted reality device designed to provide front-line workers with real-time online support from a remotely located specialist (Realwear HTM-1; Realwear) during CIED assistance in distant rural areas. METHODS: This is a prospective study of patients requiring CIED interrogation using the Realwear HMT-1 in a remote rural population in Colombia between April 2021 and June 2022. CIED interrogation and device programming were performed by a general practitioner and guided by a cardiac electrophysiologist. Non-CIED-related medical interventions were allowed and analyzed. The primary objective was to determine the incidence of clinically significant CIED alerts. Secondary objectives were the changes medical interventions used to treat the events found in the device interrogations regarding non-CIED related conditions. RESULTS: A total of 205 CIED interrogations were performed on 139 patients (age 69 ± 14 years; 54% female). Clinically significant CIED alerts were reported in 42% of CIED interrogations, consisting of the detection of significant arrhythmias (35%), lead malfunction (3%), and device in elective replacement interval (3.9%). Oral anticoagulation was initiated in 8% of patients and general medical/cardiac interventions unrelated to the CIED were performed in 52% of CIED encounters. CONCLUSION: Remote assistance using a commercially available assisted reality device has the potential to provide specialized healthcare to patients in difficult-to-reach areas, overcoming current difficulties associated with RM, including the inability to change device programming. Additionally, these interactions provided care beyond CIED-related interventions, thus delivering significant social and clinical impact to remote rural populations.

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With the growing need to obtain information about power consumption in buildings, it is necessary to investigate how to collect, store, and visualize such information using low-cost solutions. Currently, the available building management solutions are expensive and challenging to support small and medium-sized buildings. Unfortunately, not all buildings are intelligent, making it difficult to obtain such data from energy measurement devices and appliances or access such information. The internet of things (IoT) opens new opportunities to support real-time monitoring and control to achieve future smart buildings. This work proposes an IoT platform for remote monitoring and control of smart buildings, which consists of four-layer architecture: power layer, data acquisition layer, communication network layer, and application layer. The proposed platform allows data collection for energy consumption, data storage, and visualization. Various sensor nodes and measurement devices are considered to collect information on energy use from different building spaces. The proposed solution has been designed, implemented, and tested on a university campus considering three scenarios: an office, a classroom, and a laboratory. This work provides a guideline for future implementation of intelligent buildings using low-cost open-source solutions to enable building automation, minimize power consumption costs, and guarantee end-user comfort.

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The COVID-19 pandemic further highlighted the need to use low-cost remote monitoring procedures for medical patients. Since the results reported in the literature have shown that the use of Channel State Information (CSI) from Wi-Fi networks to remotely monitor patients can provide means to obtain a powerful medical information package in a non-invasive way and at low cost, a consistent review and analysis of the state of the art on this applied technique is developed in the present work. Initially, a mathematical overview of the CSI technology and its functional model is done. Subsequently, details about the technical approach necessary to use CSI in medical applications and a summary of the studies reported in the literature with such applications are presented. Based on the analyses and discussions carried out throughout this work, a better understanding of the current state of the art is achieved. Challenges and perspectives for future research are also highlighted.

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It is well known that power plants worldwide present access to difficult and hazardous environments, which may cause harm to on-site employees. The remote and autonomous operations in such places are currently increasing with the aid of technology improvements in communications and processing hardware. Virtual and augmented reality provide applications for crew training and remote monitoring, which also rely on 3D environment reconstruction techniques with near real-time requirements for environment inspection. Nowadays, most techniques rely on offline data processing, heavy computation algorithms, or mobile robots, which can be dangerous in confined environments. Other solutions rely on robots, edge computing, and post-processing algorithms, constraining scalability, and near real-time requirements. This work uses an edge-fog computing architecture for data and processing offload applied to a 3D reconstruction problem, where the robots are at the edge and computer nodes at the fog. The sequential processes are parallelized and layered, leading to a highly scalable approach. The architecture is analyzed against a traditional edge computing approach. Both are implemented in our scanning robots mounted in a real power plant. The 5G network application is presented along with a brief discussion on how this technology can benefit and allow the overall distributed processing. Unlike other works, we present real data for more than one proposed robot working in parallel on site, exploring hardware processing capabilities and the local Wi-Fi network characteristics. We also conclude with the required scenario for the remote monitoring to take place with a private 5G network.

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Nowadays, conventional agriculture farms lack high-level automated management due to the limited number of installed sensor nodes and measuring devices. Recent progress of the Internet of Things (IoT) technologies will play an essential role in future smart farming by enabling automated operations with minimum human intervention. The main objective of this work is to design and implement a flexible IoT-based platform for remote monitoring of agriculture farms of different scales, enabling continuous data collection from various IoT devices (sensors, actuators, meteorological masts, and drones). Such data will be available for end-users to improve decision-making and for training and validating advanced prediction algorithms. Unlike related works that concentrate on specific applications or evaluate technical aspects of specific layers of the IoT stack, this work considers a versatile approach and technical aspects at four layers: farm perception layer, sensors and actuators layer, communication layer, and application layer. The proposed solutions have been designed, implemented, and assessed for remote monitoring of plants, soil, and environmental conditions based on LoRaWAN technology. Results collected through both simulation and experimental validation show that the platform can be used to obtain valuable analytics of real-time monitoring that enable decisions and actions such as, for example, controlling the irrigation system or generating alarms. The contribution of this article relies on proposing a flexible hardware and software platform oriented on monitoring agriculture farms of different scales, based on LoRaWAN technology. Even though previous work can be found using similar technologies, they focus on specific applications or evaluate technical aspects of specific layers of the IoT stack.

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Brazil was one of the largest cocoa producers in the world, mainly supported by the South of Bahia region. After the 1980s, the witch-broom disease demolished plantations, and farmers were forced into bankruptcy. The worldwide search for gourmet cocoa has rekindled interest in this production, whose fermentation process is a key step in obtaining fine cocoa, thanks to the fact that many processing properties and sensory attributes are developed in this phase. This article presents a blockchain-IoT-based system for the control and monitoring of these events, aiming to catalog in smart contracts valuable information for improvement of the cocoa fermentation process, and future research. Blockchain is used as a distributed database that implements an application-level security layer. A proof of concept was modeled and the performance of the emulated system was evaluated in the OMNet simulator, where a technique based on the SNMP protocol was applied to reduce the amount of data exchanged and resources served/consumed in this representation. Then, a physical platform was developed and preliminary experiments were performed on a real farm, as a way to verify the improvement of the cocoa fermentation process when using a technological approach.

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Introduction: In Chile, 1 in 8 pregnant women of middle socioeconomic level has gestational diabetes mellitus (GDM), and in general, 5-10% of women with GDM develop type 2 diabetes after giving birth. Recently, various technological tools have emerged to assist patients with GDM to meet glycemic goals and facilitate constant glucose monitoring, making these tasks more straightforward and comfortable. Objective: To evaluate the impact of remote monitoring technologies in assisting patients with GDM to achieve glycemic goals, and know the respective advantages and disadvantages when it comes to reducing risk during pregnancy, both for the mother and her child. Methods: A total of 188 articles were obtained with the keywords "gestational diabetes mellitus," "GDM," "gestational diabetes," added to the evaluation levels associated with "glucose level," "glycemia," "glycemic index," "blood sugar," and the technological proposal to evaluate with "glucometerm" "mobile application," "mobile applications," "technological tools," "telemedicine," "technovigilance," "wearable" published during the period 2016-2021, excluding postpartum studies, from three scientific databases: PUBMED, Scopus and Web of Science. These were managed in the Mendeley platform and classified using the PRISMA method. Results: A total of 28 articles were selected after elimination according to inclusion and exclusion criteria. The main measurement was glycemia and 4 medical devices were found (glucometer: conventional, with an infrared port, with Bluetooth, Smart type and continuous glucose monitor), which together with digital technology allow specific functions through 2 identified digital platforms (mobile applications and online systems). In four articles, the postprandial glucose was lower in the Tele-GDM groups than in the control group. Benefits such as improved glycemic control, increased satisfaction and acceptability, maternal confidence, decreased gestational weight gain, knowledge of GDM, and other relevant aspects were observed. There were also positive comments regarding the optimization of the medical team's time. Conclusion: The present review offers the opportunity to know about the respective advantages and disadvantages of remote monitoring technologies when it comes to reducing risk during pregnancy. GDM centered technology may help to evaluate outcomes and tailor personalized solutions to contribute to women's health. More studies are needed to know the impact on a healthcare system.

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Remote monitoring platforms based on advanced health sensors have the potential to become important tools during the COVID-19 pandemic, supporting the reduction in risks for affected populations such as the elderly. Current commercially available wearable devices still have limitations to deal with heart rate variability (HRV), an important health indicator of human aging. This study analyzes the role of a remote monitoring system designed to support health services to older people during the complete course of the COVID-19 pandemic in Brazil, since its beginning in Brazil in March 2020 until November 2021, based on HRV. Using different levels of analysis and data, we validated HRV parameters by comparing them with reference sensors and tools in HRV measurements. We compared the results obtained for the cardiac modulation data in time domain using samples of 10 elderly people's HRV data from Fitbit Inspire HR with the results provided by Kubios for the same population using a cardiac belt, with the data divided into train and test, where 75% of the data were used for training the models, with the remaining 25% as a test set for evaluating the final performance of the models. The results show that there is very little difference between the results obtained by the remote monitoring system compared with Kubios, indicating that the data obtained from these devices might provide accurate results in evaluating HRV in comparison with gold standard devices. We conclude that the application of the methods and techniques used and reported in this study are useful for the creation and validation of HRV indicators in time series obtained by means of wearable devices based on photoplethysmography sensors; therefore, they can be incorporated into remote monitoring processes as seen during the pandemic.

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Background: The remote monitoring (RM) of cardiac implantable electronic devices (CIEDs) has become a common method of in-home monitoring and follow-up in high-income countries given its effectiveness, safety, convenience, and the possibility of early intervention. However, in Brazil, RM is still underutilized. Objectives: This observational study aims to demonstrate our experience of using RM in Brazil and the predictive factors of RM of CIED follow-up in Brazil. Methods: This was a prospective cohort study of patients with a CIED. Event rates are reported and clinical responses to those findings and outcomes based on the detection of RM. A logistic regression model was performed to identify predictors of more events, with P < .05 for statistical significance. Results: This study evaluated consecutive 119 patients: 30.2% with pacemakers, 42.8% with implantable cardioverter-defibrillator, 22.7% with cardiac resynchronization therapy (CRT) with defibrillator, and 3.3% with CRT with pacemaker. Events were detected in 63.9% of the cases in 29.5 ± 23 months of follow-up. The outcomes found were that 44.5% needed elective evaluation in medical treatment and 23.5% needed immediate evaluation in therapy. Logistic regression analysis showed that the groups with CRT or CRT with defibrillator (75.0%), reduced ejection fraction (76.5%), and New York Heart Association functional class ≥II (75.0%) had the highest RM event rates. Conclusions: RM proved to be effective and safe in the follow-up of patients with CIEDs in Brazil, allowing early interventions and facilitating therapeutic management.

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Due to the COVID-19 pandemic, health services around the globe are struggling. An effective system for monitoring patients can improve healthcare delivery by avoiding in-person contacts, enabling early-detection of severe cases, and remotely assessing patients' status. Internet of Things (IoT) technologies have been used for monitoring patients' health with wireless wearable sensors in different scenarios and medical conditions, such as noncommunicable and infectious diseases. Combining IoT-related technologies with early-warning scores (EWS) commonly utilized in infirmaries has the potential to enhance health services delivery significantly. Specifically, the NEWS-2 has been showing remarkable results in detecting the health deterioration of COVID-19 patients. Although the literature presents several approaches for remote monitoring, none of these studies proposes a customized, complete, and integrated architecture that uses an effective early-detection mechanism for COVID-19 and that is flexible enough to be used in hospital wards and at home. Therefore, this article's objective is to present a comprehensive IoT-based conceptual architecture that addresses the key requirements of scalability, interoperability, network dynamics, context discovery, reliability, and privacy in the context of remote health monitoring of COVID-19 patients in hospitals and at home. Since remote monitoring of patients at home (essential during a pandemic) can engender trust issues regarding secure and ethical data collection, a consent management module was incorporated into our architecture to provide transparency and ensure data privacy. Further, the article details mechanisms for supporting a configurable and adaptable scoring system embedded in wearable devices to increase usefulness and flexibility for health care professions working with EWS.

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The collapse of overhead power line guyed towers is one of the leading causes of power grid failures, subjecting electricity companies to pay considerable, high-value fines. In this way, the current work proposes a novel and complete framework for the remote monitoring of mechanical stresses in guyed towers. The framework method comprises a mesh network for data forwarding and neural networks to improve the performance of Low-Power and Lossy Networks. The method also considers the use of multiple sensors in the sensor fusion technique. As a result, the risk of collapse of guyed cable towers reduces, due to the remote monitoring and preventive actions promoted by the framework. Furthermore, the proposed method uses multiple input variable fusions, such as accelerometers and tension sensors, to estimate the tower's displacement. These estimations help address the structural health of the tower against failures (i.e., loosening of the stay cables, displacement, and vibrations) that can cause catastrophic events, such as tower collapse or even cable rupture.

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