Remote Health Monitoring System Research Articles

An IoT based Automated and Intelligent System for Patient Health

The Internet of Things (IoT) has remained extensively to connect accessible medical resources and provide smooth, dependable, and in effect of healthcare services to patients, and it has the potential to disrupt healthcare innovation. Health monitoring system using IoT application is the recent trend in medical field, by discovering the potential of the technology. Humans are incrassating the several issues and precocious death due to numerous illness, and by deficiency in providing medical treatment to the patients. To obtain the solution to this issue, a real time health monitoring system is proposed based on the recent technology such as IoT. Enhanced and intelligent healthcare system is the representation of developed and prosperous nation. The proposed method improves the monitoring system by shrinking the use of sensors, which have been attempted to exploit the new technology to obtain the solution for the healthcare problem currently society is facing, and a remote healthcare system is designed. The proposed automated and intelligent system involved with the different phases such as revealing the vitality of patient’s using sensors, sends patients data to cloud storage and thus providing it to the doctors to utilize it, which will help to access and observe the patient’s well-being improvement away from hospital locations. The proposed automated and intelligent system is used to interconnect the accessible medical resources and offer smart, reliable, and effective healthcare system to the people. An IoT architecture with customized healthcare applications have been developed to support remote health monitoring system.

Design and Implementation of Wearable Patient Health Monitoring System Using WBAN and IoT

A remote patient health monitoring system using Wireless Body Area Network (WBAN) has been proposed to detect sudden possible falls in elderly people, acquire body temperature and ECG (Electrocardiogram) via wireless sensor nodes viz an accelerometer, a temperature sensor, and 3 bipolar limb leads. These nodes carry information to a coordination node with the freedom of unconstrained movement, by allowing the nodes to interact with the host node seamlessly. Leads 2 and 3 gives an inferior view of the heart to detect a probable heart attack or MI that might occur in the inferior region. Dynamic Time Warping (DTW) has been employed in this work for the detection of ST elevation, T inversion, and deep Q on lead 2 data. Atrial fibrillation, the most common kind of arrhythmia, is anticipated from the acquired lead 2 data using the standard deviation parameter. The 3 lead ECG report is then forwarded to the doctor via email for remote monitoring and diagnostic purposes.

Fuzzy-assisted machine learning framework for the fog-computing system in remote healthcare monitoring

Health care monitoring systems have mainly depended on the internet of things (IoT) devices to collect, manage and analyze data from patients. Patients' health can be constantly monitored and controlled with the remote health monitoring systems. From these points, a Fuzzy-assisted machine learning framework (F-AMLF) with fog computing increases the effectiveness of the health care monitoring system. This paper presents an F-AMLF to recognize how device resource cost reduction is achieved while maintaining efficiency limitations. Patients can submit their demands for health care by a fuzzy assisted fog computing system. These systems use fuzzy logic to calculate how much computing capacity is needed to maintain fog and cloud projections. The F-AMLF shows the highest accuracy ratio of 93.6%, monitoring ratio of 92.5%, prediction ratio of 95.3%, data management ratio of 91.4%, and the lowest latency ratio of 19.7%, energy consumption ratio of 20.1%, and the cost-effective ratio of 21.5% compared to the existing methods.

Sensors and digital medicine in orthopaedic surgery.

Digital health principles are starting to be evident in medicine. Orthopaedic trauma surgery is also being impacted —indirectly by all other improvements in the health ecosystem but also in particular efforts aimed at trauma surgery. Data acquisition is changing how evidence is gathered and utilized. Sensors are the pen and paper of the next wave of data acquisition. Sensors are gathering wide arrays of information to facilitate digital health relevance and adoption. Early adaption of sensor technology by the nonlegacy health environment is what has made sensor driven data acquisition so palatable to the normal health care system. As it applies to orthopaedic trauma, current sensor driven diagnostics and surveillance are nowhere near as developed as in the larger medical community. Digital health is being explored for health care records, data acquisition in diagnostics and rehabilitation, wellness to health care translation, intraoperative monitoring, surgical technique improvement, as well as some early-stage projects in long-term monitoring with implantable devices. The internet of things is the next digital wave that will undoubtedly affect medicine and orthopaedics. Internet of things (loT) devices are now being used to enable remote health monitoring and emergency notification systems. This article reviews current and future concepts in digital health that will impact trauma care.

Development of a Remote Health Monitoring System to Prevent Frailty in Elderly Home-Care Patients with COPD.

Chronic obstructive pulmonary disease (COPD) is the general term used to describe respiratory diseases such as chronic bronchitis or emphysema of the lungs. COPD is known to cause the onset of frailty due to limitations of physical activity (PA) in daily life and undernutrition. Here, we report the development process of a remote health monitoring and support system employing a tablet computer (iPad), that was created to help prevent frailty in elderly home-care patients with COPD, and the results of its use by two elderly home-care COPD patients. There was a significant increase in PA duration in one participant after use of the system, compared to before use (15.2 min (8.9) vs. 24.2 min (7.4), p < 0.001). PA duration also increased in the other participant (39.7 (8.1) vs. 42.9 (12.9) min; 8.1%), although the difference was not statistically significant. The system enabled recognition of patients’ behavior modifications to promote health. It is difficult to obtain quantitative data for health support, such as for respiratory rehabilitation in elderly COPD patients living at home. However, the present results suggest that virtually connecting patients with their support networks via information and communication technology (ICT) equipment provides support for the physical aspect of their care.

Design and Implementation of Remote Health Monitoring System using IOT with GPS for Prediction and Analysis

Design and Implementation of Remote Health Monitoring System using IOT with GPS for Prediction and Analysis

Evaluation of a Smart After-Care Program for Patients with Lung Cancer: A Prospective, Single-Arm Pilot Study.

BackgroundThe efficacy of telemedicine among cancer survivors is uncertain. The Smart After-Care Program (SAP), which is an interactive, smartphone-based remote health monitoring system, was developed to help patients manage their health after leaving the hospital. This study was designed to evaluate the efficacy of our remote health care program for lung cancer patients.MethodsWe enrolled 50 patients with lung cancer. Self-monitoring devices were supplied to all patients, who were instructed to enter their daily vital signs and subjective symptoms to the Smart After-Care app. The app also provided information about rehabilitation exercises and a healthy diet for lung cancer patients. All patients received health counseling via telephone once a week and visited an outpatient clinic during weeks 6 and 12 to assess satisfaction with the SAP and changes in quality of life and physical performance.ResultsOverall satisfaction with the SAP was very high (very good, 61.9%; good, 26.2%). In the multivariate analysis to identify factors affecting satisfaction, the distance between the patient’s residence and the hospital was the only significant independent factor (p=0.013). Quality of life improved along all functional scales (p<0.05). Muscle strength significantly improved in the lower limbs (p=0.012). Two-minute walk distance also significantly improved (p=0.028).ConclusionThis study demonstrated that the SAP was acceptable for and supportive of patients with reduced pulmonary function after lung cancer treatment. The SAP was found to be particularly useful for patients living far from the hospital.

Strong and Tough PAm/SA Hydrogel with Highly Strain Sensitivity

The hydrogel is a preferred material for flexible wearable sensors. In practical application, it should have high-efficiency mechanical toughness and self-healing performance. Besides, hydrogel requires good affinity and adhesion because of its contact with the skin. In this experiment, we made an ultra-tough hydrogel with excellent cell affinity and adhesion. We used sodium alginate (SA) and polyacrylamide (PAm) mixture as a flexible base fluid. Polydopamine reduce graphene oxide (prGO) was used as conductive nanofiller, and then PAm-prGO-SA semi-interpenetrating network hydrogel was formed through Am radical polymerization. The presence of prGO endows the hydrogels with excellent electrical conductivity. Simultaneously, some non-reduced GO forms non-covalent cross-links with PAm, SA, and Polydopamine (PDA) in the hydrogel network. The stress of PAm-prGO-SA hydrogel can reach 750 KPa, and the strain is 900%. The hydrogel, combined with its excellent electrical, mechanical properties, and biocompatibility, is expected to be applied in portable, remote, and real-time health monitoring systems.

Telemedicine platform for health assessment remotely by an integrated nanoarchitectonics FePS3/rGO and Ti3C2-based wearable device

Due to the emergence of various new infectious (viral/bacteria) diseases, the remote surveillance of infected persons has become most important, especially if hospitals need to isolate infected patients to prevent the spreading of pathogens to health care personnel. Therefore, we develop a remote health monitoring system by integrating a stretchable asymmetric supercapacitor (SASC) as a portable power source with sensors that can monitor the human physical health condition in real-time and remotely. An abnormal body temperature and breathing rate could indicate a person’s sickness/infection status. Here we integrated FePS3@graphene-based strain sensor and SASC into an all-in-one textile system and wrapped it around the abdomen to continuously monitor the breathing cycle of the person. The real body temperature was recorded by integrating the temperature sensor with the SASC. The proposed system recorded physiological parameters in real-time and when monitored remotely could be employed as a screening tool for monitoring pathogen infection status.

Remote Healthcare Monitoring using Expert System

With the introduction of the novel coronavirus and the ensuing epidemic, health care has become a primary priority for all governments. In this context, the best course of action is to implement an Internet of Things (IoT)-based remote health monitoring system. As a result, IoT systems have attracted significant attention in academia and industry, and this trend is likely to continue as wearable sensors and smartphones become more prevalent. Even if the doctor is a substantial distance away, IoT health monitoring enables the prevention of illness and the accurate diagnosis of one’s current state of health through the use of a portable physiological monitoring framework that continually monitors the patient’s systolic blood pressure, blood glucose, oxygen saturation, and diastolic blood pressure. The expert system generates a diagnosis of the patient’s health status based on the sensor data. Once the patient’s sensor data is transmitted to the cloud via a WiFi module, the expert system uses it to diagnose the patient’s health status in order to facilitate any medical attention or critical care that may be required for his condition. The simulation is carried out in Matlab, and the results of the study are presented to demonstrate the suggested system’s significance.

Problems of development remote health monitoring system for patients with chronic diseases

Problems of development remote health monitoring system for patients with chronic diseases

A Validation Study on the Physiological Parameters Recorded by COVID BEEP - An Indigenous Remote Health Monitoring System Designed for COVID-19 Care in India

A Validation Study on the Physiological Parameters Recorded by COVID BEEP - An Indigenous Remote Health Monitoring System Designed for COVID-19 Care in India

Remote health monitoring system using heterogeneous networks.

This paper presents the implementation of a remote health monitoring system by using Heterogeneous Networks (HetNet), in which remote patients' vital data can be sent to the proximate hospital with very low end‐to‐end latency. To carry out the aforementioned process, patients' statistics are delivered initially from Wireless Body Area Network (WBAN) to the patients' mobile phone by using ISM band. Then, from there, contemporary networks make use of single wireless network alone to send the patients' data to the nearest hospital (even though there are multiple networks in a terrain). But, this particular network may have so much of end‐to‐end latency as a consequence of lack of resources in the network. However, in the proposed work, all the available heterogeneous Radio Access Technology (RAT) networks carry multiple patients' statistics to the nearest hospital by using either the RAT's free channels (in licensed band) or white space channels. Further, in order to reduce the latency in the proposed system, a novel hand‐off method is suggested in this paper by exploiting SDR features. Moreover, simulation results reveal the effectiveness of the proposed system in terms of end‐to‐end latency and spectral efficiency.

Research and Development of an IoT-Based Remote Asthma Patient Monitoring System.

This paper presents the research and development of an Internet of Things- (IoT-) based remote health monitoring system for asthmatic patients. Asthma is an inflammatory disease. Asthma causes the lungs to swell and get narrower, making it difficult to carry air in and out of the lungs. This situation makes breathing very difficult. Remote patient monitoring (RPM) is a method of collecting health-related data from patients who are in a remote location and electronically transmitting it to healthcare providers for evaluation and consultation. The aim of this study is to design a monitoring system that allows doctors to monitor asthmatic patients from a remote area. The proposed system will allow patients to measure oxygen saturation (SpO2), heart rate, body temperature, humidity, volatile gases, room temperature, and electrocardiogram (ECG) using various sensors, which will be displayed in an application. This data is then sent to the doctor to monitor the patient's condition and suggest appropriate actions. Overall, the system consists of an Android application, a website, and various sensors. The Android studio and Java programming language were used to develop the application. For the frontend, the website was built using Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), JavaScript, and jQuery. The system also uses Django, a Python-based open-source web framework, for the backend. The system developed the various sensors using an ESP8266 microcontroller compatible with the Arduino Integrated Development Environment (IDE). The system uses a MAX30100 pulse oximeter and heart rate sensor, a GY-906 MLX90614 noncontact precision thermometer, a DHT11 humidity and temperature sensor, a MQ-135 gas and air quality sensor, and an AD8232 ECG sensor for collecting various parameters that may trigger asthma attacks. Finally, the system developed the Asthma Tracker app and the Asthma Tracker website for remote health monitoring. The system was initially tested on demo patients and later deployed and tested on seven real human test subjects. Overall, the monitoring system produced satisfactory results. The data acquired by the sensors has a high level of accuracy. The system also maintained user-friendliness and low cost.

Epidemiology of Coronavirus Disease Outbreak among Crewmembers on Cruise Ship, Nagasaki City, Japan, April 2020.

In April 2020, a coronavirus disease (COVID-19) outbreak occurred on the cruise ship Costa Atlantica in Nagasaki, Japan. Our outbreak investigation included 623 multinational crewmembers onboard on April 20. Median age was 31 years; 84% were men. Each crewmember was isolated or quarantined in a single room inside the ship, and monitoring of health status was supported by a remote health monitoring system. Crewmembers with more severe illness were hospitalized. The investigation found that the outbreak started in late March and peaked in late April, resulting in 149 laboratory-confirmed and 107 probable cases of infection with severe acute respiratory syndrome coronavirus 2. Six case-patients were hospitalized for COVID-19 pneumonia, including 1 in severe condition and 2 who required oxygen administration, but no deaths occurred. Although the virus can spread rapidly on a cruise ship, we describe how prompt isolation and quarantine combined with a sensitive syndromic surveillance system can control a COVID-19 outbreak.

Internet of Things (IoT) Based Smart Health Monitoring System – A Case Study

A new corona virus has heightened awareness of the need of health care in every country. IoT-based health monitoring systems are the greatest option in this regard. In particular, health care researchers are increasingly interested in the Internet of Things (IoT). Remote health care monitoring has grown at such a rapid pace due to the increasing usage of wearable sensors and smart phones. Even if a doctor is far away, IoT health monitoring can assist prevent the spread of disease and provide an accurate diagnostic of the status of health. Authorized individuals can access this data saved on any IoT platform and diagnose illnesses based on these values obtained from a distance using the suggested remote health monitoring system

IOT based Remote Health Monitoring System

As the technology changing every year so, there has been an attempt to apply the new technology in numerous areas to increase the quality of human life. One of the main fields of research that has seen an implementation of the technology is the healthcare sector. Consequently, our paper is an effort to solve a healthcare problem currently people are facing. Main objective of our paper is to enterprise a remote healthcare system. It covers of three key parts. The first part is, detection of patient’s condition with the proposed system, second is to storing data on cloud storage and the last part is to provide the data for isolated viewing. Remote observing of the data empowers a doctor or custodian to television a patient’s health advancement from anywhere. In this project, we have obtainable an IoT architecture personalized for healthcare applications. The main motive of this scheme is to come up with a Remote Health Monitoring System that will completed with locally available sensors with a view to manufacture it reasonable for everybody

Remote Health Monitoring During and After the COVID-19 Pandemic.

High importance of the remote health monitoring (RHM) especially during and after the pandemic is accentuated in this article. It is displayed that by this way it is possible to revealing automatically situations "suspicious" from the COVID-19 illness view point for some concrete patients and also to keep up with possible complications after the illness. Another great opportunity of the RHM is connected with investigation of the vaccines. RHM allows reveal cases of the complications among the patients as well as positive and negative consequences of the vaccination. The general depersonalized data should be gathered and analyzed to research the regularities of the COVID-19 sickness rate and the complications frequency and also of the safety and effectiveness of the vaccines. It is proposed to combine advantages of RHM for medical care for concrete patients with opened opportunities for research to reveal important general normality connected with correlation between COVID-19 complications and peculiarities of various chronic diseases and specific medical statements. Telemedicine platform intended for creation of RHM systems is described. It has gone through the pilot running in Russian medical institutions and now presented good results have been achieved.

IoT Based Remote Health Monitoring and Alert System

Since they are isolated in their later years, most people are still forgotten and powerless in medical crises. To deal with this, we've devised a potential Remote Health Monitoring and Warning System (RHMAS). Heart attacks in the elderly are linked with complications such as body temperature changes, elevated blood pressure, profuse sweating, and an abnormal cardiac rhythm, among others. Our approach is to include sophisticated sensors capable of detecting and tracking these signs in order to warn family members, kin, family practitioner, and health care in the event of an emergency. Since most gadgets for this reason are wired, a wireless interface does not obstruct the user's movement. The suggested device includes a Photo-Plethysmography (PPG) dependent pulse sensor to identify arrhythmia, a temperature sensor to continuously track their body temperature, a pressure sensor to sense blood pressure ranges, and a heartbeat sensor. If the controlled data deviates from the nominal body state, an ESP 8266 module can give a message to the next of kin. If the tracked data hits emergency thresholds, health providers can send a message to her kin as well as a buzzer to a consent user.

An IoT and fog computing enabled intelligent health care monitoring system to optimize the cloud storage

Health is on eof the main characteristic of quantity of life, hence the significance of having an appropriate healthcare monitoring system. The Internet of Things (IoT) is a state of the art technology that has found application in modern remote health monitoring systems. Fog computing is given to IoT by producing the local computing. Fog computing serves to overcome high latency and consumption of bandwidth in the cloud. Remote operation and connection is the heart of health monitoring application where real time information exchange is key. However, there is often delay due to the transfer of the information to the cloud and back to request which is intolerable. So a technique is heareby proposed to incoperate the fog computing techniques amongst cloud computing and the sensors to process information and to collect it efficiently. The sensor nodes are collected and detected by using the global monitoring capability to trace and detect the moving sensors which can be achieved by fog computing. With this design, there is minimal amount of data transfer between the sensor and node which increases the system efficiency. The task scheduling algorithm has the ability in which the main factor provide importance to perform the task exactly. Thus the algorithm is further augmented with a system called Task Classification and Virtual machines Categorization (TCVC) which applied a MAX-MIN concept to schedule the important tasks to optimize the cloud storage and reduce the latency and time on fog computing.