Remote Monitoring Applications Research Articles

TeleCleft: Development and Evaluation of a Mobile Application for Monitoring Cleft Patients.

Development and evaluation of a mobile application for remote monitoring and guidance of pediatric patients diagnosed with cleft lip and/or palate (CL ± P) and their caregivers. This is a pilot cross-sectional, applied, and quantitative study. The study was conducted in two tertiary care treatment centers in Brazil. The participants included 20 caregivers and infants undergoing treatment with nasoalveolar molding (NAM) for CL ± P. The intervention involved using the TeleCleft mobile application for remote monitoring and guidance of caregivers and infants during NAM treatment. The main outcome measures included usability and satisfaction of users with the TeleCleft application. The results showed high usability and satisfaction ratings among users of the TeleCleft application. Most participants found remote monitoring to be effective and expressed positive opinions about its convenience and usefulness. TeleCleft could be a viable tool for remote monitoring and guidance, reducing the need for patients and caregivers to travel to treatment centers, which could potentially alleviate the burden of care faced by families during the journey of CL ± P treatment.

Impact of the use of a smartphone‐based blood glucose management system within a maternal diabetes service

AbstractBackground: The incidence of gestational diabetes mellitus is increasing, placing more demand on pregnancy diabetes services.Aims: This study aimed to explore the impact of implementing GDm‐Health, a remote blood glucose monitoring application (app), on a tertiary pregnancy diabetes service.Methods: This retrospective cohort study was conducted as part of a quality improvement project. We assessed the frequency of interactions between patients and health care professionals, the type of interactions (face‐to‐face [f2f] or non‐f2f [via text or phone call]), effect on time to treatment initiation and women's satisfaction with the app. We compared two cohorts: cohort 1, women diagnosed in September 2019 (n=52) prior to app introduction, and cohort 2, women diagnosed in September 2020 (n=54) after app introduction. Data were collected from the electronic notes, and app satisfaction was assessed using a questionnaire.Results: Median interactions for each woman from diagnosis to delivery increased from 5 (interquartile range [IQR], 3–6) in cohort 1 to 7 (IQR, 5–10) in cohort 2 (p<0.001). In cohort 2, 88.4% of interactions were non‐f2f compared to 13.7% in cohort 1. There was no change in the time to treatment initiation (19 days [cohort 1] vs 20 days [cohort 2]; p=0.59). Women using the app were satisfied with their care.Conclusions: After GDm‐Health was introduced, women had more interactions with the diabetes team; however, most were non‐f2f interactions via telephone. The app has helped health care professionals streamline the service, particularly in terms of the allocation of clinic space and appointments, and has been well received by patients.

Au-decorated Ti3C2Tx/porous carbon immunoplatform for ECM1 breast cancer biomarker detection with machine learning computation for predictive accuracy

Electrochemical immunosensors, surpassing conventional diagnostics, exhibit significant potential for cancer biomarker detection. However, achieving a delicate balance between signal sensitivity and operational stability, especially at the heterostructure interface, is crucial for practical immunosensors. Herein, porous carbon (PC) integration with Ti3C2Tx-MXene (MX) and gold nanoparticles (Au NPs) constructs a versatile immunosensing platform for detecting extracellular matrix protein-1 (ECM1), a breast cancer-associated biomarker. The inclusion of PC provided robust structural support, enhancing electrolytic diffusion with an expansive surface area while synergistically facilitating charge transfer with Ti3C2Tx. The biosensor optimized with 1.0 mg PC demonstrates a robust electrochemical redox response to the surface-bound thionine (th) redox probe, utilizing an inhibition-based strategy for ECM1 detection. The robust antibody-antigen interactions across the PC-integrated Ti3C2Tx-Au NPs platform (MX-Au-C-1) enabled robust ECM1 detection within 0.1–7.5 nM, with a low limit of detection (LOD) of 0.012 nM. The constructed biosensor shows improved operational stability with a 98.6 % current retention over 1 h, surpassing MXene-integrated (MX-Au) and pristine Au NPs (63.2 % and 44.3 %, respectively) electrodes. Moreover, the successful adaptation of the artificial neural network (ANN) model for predictive analysis of the generated DPV data further validates the accuracy of the biosensor, promising its future application in AI-powered remote health monitoring.

Development of an unmanned ground vehicle for seed planting

As global population growth intensifies the demand for sustainable food production, the application of robotics to agriculture emerges as a promising solution. This research focuses on the design, development, and deployment of an unmanned ground vehicle for seed planting, also known as a robotic seed planter. The robotic seed planter automates seed planting processes, offering advantages such as increased accuracy, reduced labour requirements, and optimal resource usage. Parametric Technology Corporation (PTC) Creo was used for the structural design, Proteus 8.14 for the circuitry design, and Arduino IDE 2.0 with Visual Studio Code for the programming. The design incorporates seed metering and drilling mechanisms guided by intelligent systems. Results show exceptional accuracy in seed placement (94%), operational efficiency, and adaptability to diverse conditions, with energy consumption relatively low. The planter is equipped with a web application for remote monitoring and control. The application is hosted on one of the microcontrollers and WebSockets protocol is utilized for inter-microcontroller communication. It offers an auto mode for automated planting and Manual mode for easier manoeuvrability. The findings of this study demonstrate the robotic seed planter’s transformative impact on precision agriculture, providing a glimpse into the future of efficient and sustainable farming operations.

Hot‐spot aware multicost‐based energy‐efficient routing protocol for WBANs

SummaryWireless body area networks (WBANs) are becoming widely considered in remote healthcare monitoring applications. However, WBAN nodes have limited resources; therefore, effective and reliable routing protocols are pivotal research challenges. Furthermore, balancing the traffic load among sensor nodes is also highly required to increase network stability. In recent years, many interesting routing solutions have been proposed for WBANs; however, the significant feature in terms of stability and energy in these solutions has not been sufficiently addressed. Therefore, in this context, the Hot‐Sspot Aaware Multicost‐based Energy‐efficient Routing (H‐SAMER) protocol is proposed in this paper. The suggested protocol used multieffective cost function for next‐hop node selection based on the data type, where the patient's data are categorized into three classes: normal data, on‐demand data, and emergency data. Furthermore, the H‐SAMER protocol adds awareness to the transmission of control packets by adding the cost value to the RREQ packets. Thus, the simulation scenario shows that the H‐SAMER saves energy 8.57%, 88%, 98%, 97%, and 100% greater than E‐HARP, EH‐RCP, CO‐LAEEBA, EECBSR, and ELR‐W, respectively. Moreover, the first node death of the proposed H‐SAMER is delayed to round number 7500, which proves H‐SAMER to be a stable and reliable effective solution for WBANs.

Evaluation of Patient Experiences with PocDoc, a Web-Based Eye Screening Tool.

The efficacy of diagnostic and monitoring tools in ophthalmology is significantly influenced by patient engagement levels. This presents a notable challenge, especially in the context of developing tools designed for telemedicine applications. Ensuring consistent patient engagement is therefore crucial for the accurate and reliable utilization of these technologies. This study assesses patient perceptions and experiences after using a purpose-built web application, called PocDoc. A cross-sectional questionnaire-based survey was conducted among 440 patients recruited from general and specialist eye clinics between March 2022 and October 2023, both before and after using the PocDoc app. Pre-test findings revealed that 86.8% of patients thought that a remote eye monitoring application would have use, while 70.9% anticipated frequent usage. Only 16.4% found it overly complex, and 55.2% perceived it as easy to use. Additionally, 34.5% foresaw the need for technical support, while 72.5% believed they would quickly grasp its use. In the post-test questionnaire, 63.3% of patients still expressed intent for frequent PocDoc usage. The perception of complexity decreased to 20.4%, with 79.3% finding it easy to use. The belief in the need for technical support decreased to 36.5%, while 89.9% felt confident in mastering the application quickly. Moreover, 77.3% found the application's functions well-integrated, and 64.6% were very confident using PocDoc. Results suggest patient receptivity to web-based applications, confirming their viability for specific patient groups. Overall, our study contributes to the growing body of evidence indicating that greater exposure to digital health tools can significantly influence patient acceptance and perceived ease of use, an insight that has important implications for the implementation and design of these technologies in clinical settings.

Wireless Technologies in Flexible and Wearable Sensing: From Materials Design, System Integration to Applications.

Wireless and wearable sensors attract considerable interest in personalized healthcare by providing a unique approach for remote, noncontact, and continuous monitoring of various health-related signals without interference with daily life. Recent advances in wireless technologies and wearable sensors have promoted practical applications due to their significantly improved characteristics, such as reduction in size and thickness, enhancement in flexibility and stretchability, and improved conformability to the human body. Currently, most researches focus on active materials and structural designs for wearable sensors, with just a few exceptions reflecting on the technologies for wireless data transmission. This review provides a comprehensive overview of the state-of-the-art wireless technologies and related studies on empowering wearable sensors. The emerging functional nanomaterials utilized for designing unique wireless modules are highlighted, which include metals, carbons, and MXenes. Additionally, the review outlines the system-level integration of wireless modules with flexible sensors, spanning from novel design strategies for enhanced conformability to efficient transmitting data wirelessly. Furthermore, the review introduces representative applications for remote and noninvasive monitoring of physiological signals through on-skin and implantable wireless flexible sensing systems. Finally, the challenges, perspectives, and unprecedented opportunities for wireless and wearable sensors are discussed.

A near-zero quiescent power breeze wake-up anemometer based on a rolling-bearing triboelectric nanogenerator

AbstractWind sensors have always played an irreplaceable role in environmental information monitoring and are expected to operate with lower power consumption to extend service lifetime. Here, we propose a breeze wake-up anemometer (B-WA) based on a rolling-bearing triboelectric nanogenerator (RB-TENG) with extremely low static power. The B-WA consists of two RB-TENGs, a self-waking-up module (SWM), a signal processing module (SPM), and a wireless transmission unit. The two RB-TENGs are employed for system activation and wind-speed sensing. Once the ambient wind-speed exceeds 2 m/s, the wake TENG (W-TENG) and the SWM can wake up the system within 0.96 s. At the same time, the SPM starts to calculate the signal frequency from the measured TENG (M-TENG) to monitor the wind speed with a sensitivity of 9.45 Hz/(m/s). After the wind stops, the SWM can switch off the B-WA within 0.52 s to decrease the system energy loss. In quiescent on-duty mode, the operating power of the B-WA is less than 30 nW, which can greatly extend the service lifetime of the B-WA. By integrating triboelectric devices and rolling bearings, this work has realized an ultralow quiescent power and self-waked-up wireless wind-speed monitoring system, which has foreseeable applications in remote weather monitoring, IoT nodes, and so on.

Quality measures of virtual care in ambulatory healthcare environments: a scoping review

ObjectivesDelivery of virtual care increased throughout the COVID-19 pandemic and persisted after physical distancing measures ended. However, little is known about how to measure the quality of virtual care, as...

Smart spirits: an integrated IoT-based liquor and health monitoring system

This project entails the development of a comprehensive health monitoring system utilizing Arduino Uno, a range of sensors (including alcohol, pulse, and DHT11), an LCD display, and a GSM module for data transmission to the Thingspeak application. Its objective is to monitor vital health parameters such as temperature, humidity, pulse rate, and alcohol levels in real-time, accessible via the Thingspeak mobile app. Key components include an Arduino Uno microcontroller, DHT11 sensor for temperature and humidity, pulse sensor for heart rate, alcohol sensor for detecting alcohol levels, LCD display for immediate feedback, and a GSM module for remote data transmission. The user-friendly Thingspeak app serves as an interface for seamless health metric monitoring. The system operates by collecting sensor data, displaying it locally on the LCD screen, and simultaneously transmitting it to the Thingspeak app via GSM communication. Users can then access the app to visualize and monitor their health metrics in real-time, allowing for prompt interventions or medical assistance if needed. The code implementation integrates sensor readings, LCD display control, and Thingspeak functionality. Leveraging Thingspeak's cloud-based platform enhances usability and accessibility, making remote health monitoring feasible. This system offers a versatile solution for individuals looking to efficiently track and manage their well-being, thanks to the integration of Arduino Uno, sensors, Thingspeak features, and GSM communication, making it suitable for both local and remote health monitoring applications.

Resource-aware fog service placement using deferred acceptance in edge computing

Fog computing aims at reducing network latency, bandwidth and processing delay by bringing computation resources closer to the data sources. Modern IoT applications, such as smart surveillance systems, remote health monitoring applications, ambient-aware applications etc., are time-critical and computationally intensive. For such applications, it is ideal to consider an intermediate layer of processing i.e a fog layer in addition to cloud. However, processing the workload of such IoT applications with an intermediate layer of fog nodes has several challenges. The significant challenges include the mobility of end-user nodes, dynamic patterns of workload generation leading to highly-variant resource requirements and sensitive quality of service (QOS) requirements. Hence a dynamic approach is required to precisely map the service requests from end-user devices to a suitable fog node. The optimality of a fog node for service placement depends on several factors, including location, resource utilization rates such as CPU, Memory and Disk utilization % and energy consumption. Several meta-heuristic techniques and evolutionary algorithms have been proposed in the past for optimal service placement among fog nodes. This paper investigates the applicability of a game theory-based approach called Deferred acceptance (DA) for the same. The DA algorithm, originally designed as a stable matching mechanism for the marriage market is adapted for service placement problems in fog-based IoT systems. The effectiveness of optimized service placement through the DA approach is validated experimentally. The experiment is carried out by creating a test bed that mimics a fog computing-based intelligent traffic management application. The proposed approach's performance is evaluated through parameters such as the startup time for the DA approach to produce outcomes, total execution time and handshake latency. The numerical results of the DA approach are compared with those of a simple scheduling algorithm ( FIFO) and a basic genetic algorithm-based approach. The DA approach appears to perform on par with the genetic algorithm in terms of start-up time, but exceeds the genetic algorithm with respect to stability of the outcomes produced.

Multipurpose Modular Wireless Sensor for Remote Monitoring and IoT Applications.

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.

Performance of a combined electrotrophic and electrogenic biofilm operated under long-term, continuous cycling.

Evaluate electrochemically active biofilms as high energy density rechargeable microbial batteries toward providing persistent power in applications where traditional battery technology is limiting (, remote monitoring applications). Here we demonstrated that an electrochemically active biofilm was able to store and release electrical charge for alternating charge/discharge cycles of up to 24h periodicity (50% duty cycle) with no significant decrease in average current density (0.16 ± 0.04 A/m2) for over 600days. However, operation at 24h periodicity for > 50days resulted in a sharp decrease in the current to nearly zero. This current crash was recoverable by decreasing the periodicity. Overall, the coulombic efficiency remained near unity within experimental error (102 ± 3%) for all of the tested cycling periods. Electrochemical characterization here suggests that electron transfer occurs through multiple routes, likely a mixture of direct and mediated mechanisms. These results indicate that bidirectional electrogenic/electrotrophic biofilms are capable of efficient charge storage/release over a wide range of cycling frequency and may eventually enable development of sustainable, high energy density rechargeable batteries.

Discriminative detection of glucose and urea with a composite polymer nanofiber based matrix

AbstractDetection and quantification of glucose and urea are fundamental in medical analysis, real‐time monitoring, and point of care analysis. However, such analyses generally require sophisticated instrumentation and specialized personnel. Furthermore, discriminative detection of multiple analytes is often necessary for treatment and diagnosis. To address this challenge, this study describes a proof‐of‐concept for discriminative sensitive amperometric detection of both analytes. This was achieved by the fabrication of a polymer‐MWCNTs composite nanofiber matrix upon which glucose oxidase (GOD) and urease were co‐immobilized to allow detection of the corresponding substrates (glucose and urea). The (PAN(−MWCNTs)/Urease‐GOD) biosensor showed good performance in: (i) glucose biosensing with sensitivity of 31±5 μAmM−2cm−2 within an extended linear range (0.1–5.0 mM) and a limit of detection of 3.7 μM, and (ii) urea detection at very low concentration (4–30 and 30–90 μM) with sensitivity up to 350±19 μAmM−2cm−2 and very low LOD (0.1 μM). The analogous mono‐enzyme platform for urea detection (PAN(−MWCNTs)/Urease) showed very similar performance as the bi‐enzyme sensor, suggesting little to no influence of co‐immobilization on Urease activity, thus confirming that the two catalytic processes are independent of each other. The biosensors exhibited high accuracy in the detection of both analytes (at normal and pathological levels) in human serum, thus proving that the biosensor described herein can have practical applications in healthcare and remote patient monitoring.

The advantages, disadvantages, threats, and opportunities of electronic patient-reported outcome systems in cancer: A systematic review.

Electronic patient-reported outcome (ePRO) systems hold promise for revolutionizing communication between cancer patients and healthcare providers across various care settings. This systematic review explores the multifaceted landscape of ePROs in cancer care, encompassing their advantages, disadvantages, potential risks, and opportunities for improvement. In our systematic review, we conducted a rigorous search in Scopus, Web of Science, and PubMed, employing comprehensive medical subject heading terms for ePRO and cancer, with no date limitations up to 2024. Studies were critically appraised and thematically analyzed based on inclusion and exclusion criteria, including considerations of advantages, disadvantages, opportunities, and threats. Analyzing 85 articles revealed 69 themes categorized into four key areas. Advantages (n = 14) were dominated by themes like "improved quality of life and care." Disadvantages (n = 26) included "limited access and technical issues." Security concerns and lack of technical skills were prominent threats (n = 10). Opportunities (n = 19) highlighted advancements in symptom management and potential solutions for technical challenges. This review emphasizes the crucial role of continuous exploration, integration, and innovation in ePRO systems for optimizing patient outcomes in cancer care. Beyond traditional clinical settings, ePROs hold promise for applications in survivorship, palliative care, and remote monitoring. By addressing existing limitations and capitalizing on opportunities, ePROs can empower patients, enhance communication, and ultimately improve care delivery across the entire cancer care spectrum.

Application of remote monitoring of biosignals and geolocation with a Wearable for patients with sequelae of the coronavirus

<span lang="EN-US">Several patients who have overcome coronavirus disease (COVID-19) have been left with cardiovascular and pulmonary sequelae and most medical centers lack a remote monitoring system for each patient that notifies them of any complications during rehabilitation. The objective of this research was to implement a Wearable that monitors the patient's health and alerts in case of detecting any anomaly. For this reason, a Wearable was developed that displays the patient's heart rate, oxygen saturation level and body temperature on the Light Emitting Diode (LCD) and the application mobile, sending an alert and geolocation message if anomalies are detected in vital signs. The standard deviation of heart rate, temperature and oxygen saturation was obtained, which was 1.4930, 0.1558 and 0.4364 in the rest stage, respectively, and 6.3442, 0.2365 and 0.9186 in the physical activity stage respectively with a maximum duration of 42 hours and 52 minutes of battery, managing to send alert messages and store the information in the cloud, which allows to conclude that the Wearable can facilitate the management of the database and the location of the patient, that the measurement error increases with physical activity, and that battery life varies with the number of biosignal readings per hour.</span>

Remote Symptom Monitoring to Enhance the Delivery of Palliative Cancer Care in Low-Resource Settings: Emerging Approaches from Africa.

This paper brings together researchers, clinicians, technology developers and digital innovators to outline current applications of remote symptom monitoring being developed for palliative cancer care delivery in Africa. We outline three remote symptom monitoring approaches from three countries, highlighting their models of delivery and intended outcomes, and draw on their experiences of implementation to guide further developments and evaluations of this approach for palliative cancer care in the region. Through highlighting these experiences and priority areas for future research, we hope to steer efforts to develop and optimise remote symptom monitoring for palliative cancer care in Africa.

Raspberry Pi Based Smart Humidifier with Model Prediction

This work is based on Raspberry Pi and implements three main functions, namely temperature and humidity measurement, automatic switching on or off of the humidification module beyond the threshold, and anti-dry burning warning. The temperature and humidity sensor and pressure sensor receive the data and display it in real time on the serial port monitor. After the data is sent to the serial port, the WiFi module can transmit the data to the mobile phone application for remote real-time monitoring and surveillance. When the mobile phone detects insufficient water in the humidifier, it turns on the operation pump and pumps a fixed amount of water into the humidifier. At the same time, the data detected by the sensor is put into the deep learning model, and the predicted data is analysed to achieve the effect of pre-humidification and regulating the balance of environmental parameters.

Comparative Study of Vital Sign Monitoring Techniques and Methods Using Radar Sensor

Abstract: COVID-19 (Corona Virus Disease of 2019) is a global pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) virus. This disease has significantly impacted every aspect of people's lives, including their work style, leisure activities, and use of technology. Additionally, due to psychological factors or other reasons, there has been a surge in deaths from cardiovascular failure during the pandemic. As COVID-19 is a silent killer whose symptoms only become visible after significant damage has been done, constant monitoring of heart parameters is crucial to address this issue. This paper explores the emerging trends in monitoring vital signs such as the electrocardiogram (ECG), heart rate, respiration rate (breaths), related sensors, remote sensor organization, and telemedicine innovations. Furthermore, this paper discusses the potential application of non-contact radar-based remote monitoring for vital sign monitoring of affected patients.

A full privacy-preserving distributed batch-based certificate-less aggregate signature authentication scheme for healthcare wearable wireless medical sensor networks (HWMSNs)

AbstractThe dynamic connectivity and functionality of sensors has revolutionized remote monitoring applications thanks to the combination of IoT and wireless sensor networks (WSNs). Wearable wireless medical sensor nodes allow continuous monitoring by amassing physiological data, which is very useful in healthcare applications. These text data are then sent to doctors via IoT devices so they can make an accurate diagnosis as soon as possible. However, the transmission of medical text data is extremely vulnerable to security and privacy assaults due to the open nature of the underlying communication medium. Therefore, a certificate-less aggregation-based signature system has been proposed as a solution to the issue by using elliptic curve public key cryptography (ECC) which allows for a highly effective technique. The cost of computing has been reduced by 93% due to the incorporation of aggregation technology. The communication cost is 400 bits which is a significant reduction when compared with its counterparts. The results of the security analysis show that the scheme is robust against forging, tampering, and man-in-the-middle attacks. The primary innovation is that the time required for signature verification can be reduced by using point addition and aggregation. In addition, it does away with the reliance on a centralized medical server in order to do verification. By taking a distributed approach, it is able to fully preserve user privacy, proving its superiority.