Patient Health Monitoring System Research Articles

Patient Health Monitoring System Development using ESP8266 and Arduino with IoT Platform

Patient Health Monitoring System Development using ESP8266 and Arduino with IoT Platform

Remote Health Care Monitoring System using IoT for Asthma/Heart Patients

Abstract: Healthcare has now become a big concern in almost everyone's socioeconomic routine. With the digitalization of lifestyle, the era of modern human evaluation began, making people robust and machine dependent. This leads to the numerous amounts of data that are scattered everywhere in each and every move in his day-to-day life. Digitization transformed basic information technology into intelligent technology by altering human lifestyle. Additionally, the world's population is expanding, which means the occurrence of numerous chronic heart illnesses. Consequently, more people get sick, hospitals are congested, and the death rate rises. Additionally, this technology transmits real-time data on patients' heartbeat and temperature with records over the Internet. Therefore, a patient health monitoring system based on IoT uses the internet to efficiently monitor patient health. It also allows users to monitor their loved ones while they are at work and has even saved lives. Also, NodeMCU is used as the web server to track patient health while using this monitoring system. Consequently, patient health indicators like body temperature, heart rate, and blood oxygen level are get monitored and stores the data. Also, Big data is a concept that can be applied to better health monitoring.

Fuzzy-logic-based IoMT framework for COVID19 patient monitoring

Smart healthcare is an integral part of a smart city, which provides real time and intelligent remote monitoring and tracking services to patients and elderly persons. In the era of an extraordinary public health crisis due to the spread of the novel coronavirus (2019-nCoV), which caused the deaths of millions and affected a multitude of people worldwide in different ways, the role of smart healthcare has become indispensable. Any modern method that allows for speedy and efficient monitoring of COVID19-affected patients could be highly beneficial to medical staff. Several smart-healthcare systems based on the Internet of Medical Things (IoMT) have attracted worldwide interest in their growing technical assistance in health services, notably in predicting, identifying and preventing, and their remote surveillance of most infectious diseases. In this paper, a real time health monitoring system for COVID19 patients based on edge computing and fuzzy logic technique is proposed. The proposed model makes use of the IoMT architecture to collect real time biological data (or health information) from the patients to monitor and analyze the health conditions of the infected patients and generates alert messages that are transmitted to the concerned parties such as relatives, medical staff and doctors to provide appropriate treatment in a timely fashion. The health data are collected through sensors attached to the patients and transmitted to the edge devices and cloud storage for further processing. The collected data are analyzed through fuzzy logic in edge devices to efficiently identify the risk status (such as low risk, moderate risk and high risk) of the COVID19 patients in real time. The proposed system is also associated with a mobile app that enables the continuous monitoring of the health status of the patients. Moreover, once alerted by the system about the high risk status of a patient, a doctor can fetch all the health records of the patient for a specified period, which can be utilized for a detailed clinical diagnosis.

Internet of things based real-time coronavirus 2019 disease patient health monitoring system

<span lang="EN-US">The coronavirus disease (COVID-19) outbreak has led to many infected worldwide and has become a global crisis. COVID-19 manifests in the form of shortness of breath, coughing and fever. More people are getting infected and healthcare systems worldwide are overwhelmed as healthcare workers become exhausted and infected. Thus, remote monitoring for COVID-19 patients is required. An internet of things (IoT) based real-time health monitoring system for COVID-19 patients was proposed. It features monitoring of five physiological parameters, namely electrocardiogram (ECG), heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2) and body temperature. These vitals are processed by the main controller and transmitted to the cloud for storage. Healthcare professionals can read real-time patient vitals on the web-based dashboard which is equipped with an alert service. The proposed system was able to transmit and display all parameters in real-time accurately without any packet loss or transmission errors. The accuracy of body temperature readings, RR, SpO2 and HR, is up to 99.7%, 100%, 97.97% and 98.34%, respectively. Alerts were successfully sent when the parameters reached unsafe levels. With the proposed system, healthcare professionals can remotely monitor COVID-19 patients with greater ease, lessen their exposure to the pathogen, and improve patient monitoring.</span>

Development of health monitoring system using smart intelligent device

Electronic technology plays a vital role in healthcare, not only for sensory equipment but also for communication and recording. As a result, the Internet of Things (IoT) is the most recent communication breakthrough in healthcare. In this work, we present a system that tracks patient health using a Blynk application, a micro-controller as a communication gateway, and sensors. When the output of the detector changes, a buzzer is embedded into the controller to alert the nursing staff. The sensor connects to a micro-controller, which is then interfaced with the liquid-crystal display (LCD) panel and wireless local area network (LAN) to provide notifications. An alert will be sent to the doctor through IoT if the system detects a change in the patient’s pulse rate or blood pressure, and the patient’s heartbeat, blood pressure, and body temperature will be displayed in real-time via Cloud. As a result, an IoT-based patient health monitoring system could save lives by efficiently monitoring patients’ health in real- time.

Heartbeat and Temperature Monitoring System

Abstract: A Major subject of concern in the medical field is to save lives of patient as soon as possible. Improper care, late detection, slow diagnosis and expensive machineries are reasons of most deaths of patients. Saving lives had become challenging work without the help of technology. As a remedy to this we came up with a solution of patient health monitoring system which will keep track of various health components of patient. The system is very portable and can be manufactured at low cost. This system is also capable to monitor oxygen level of body. The device will work on Internet of things technology. This device is implemented using NODE MCU board. And the device will be connected to WiFi, with help of which the data will be sent over to internet over to Blynk cloud platform. With which the data can be monitored from anywhere at any time. And also emergency message alerts will be sent as email over registered email address to get emergency updates with help of Blynk app.

Novel Internet of Things based approach toward diabetes prediction using deep learning models.

The integration of the Internet of Things with machine learning in different disciplines has benefited from recent technological advancements. In medical IoT, the fusion of these two disciplines can be extremely beneficial as it allows the creation of a receptive and interconnected environment and offers a variety of services to medical professionals and patients. Doctors can make early decisions to save a patient's life when disease forecasts are made early. IoT sensor captures the data from the patients, and machine learning techniques are used to analyze the data and predict the presence of the fatal disease i.e., diabetes. The goal of this research is to make a smart patient's health monitoring system based on machine learning that helps to detect the presence of a chronic disease in patient early and accurately. For the implementation, the diabetic dataset has been used. In order to detect the presence of the fatal disease, six different machine learning techniques are used i.e., Support Vector Machine (SVM), Logistic Regression, Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM). The performance of the proposed model is evaluated by using four evaluation metrics i.e., accuracy, precision, recall, and F1-Score. The RNN outperformed remaining algorithms in terms of accuracy (81%), precision (75%), and F1-Score (65%). However, the recall (56%) for ANN was higher as compared to SVM and logistic regression, CNN, RNN, and LSTM. With the help of this proposed patient's health monitoring system, doctors will be able to diagnose the presence of the disease earlier.

IOT Based Patient Health Monitoring System

Abstract: Patients are facing a problematic situation of unforeseen demise due to the specific reason of heart problems and attack which is because of non existence of good medical maintenance to patients at the needed time. This is for specially monitoring old age patients and informing doctors and loved ones. So, we are proposing an innovative project to dodge such sudden death rates by using Patient Health Monitoring that uses sensor technology and uses the internet to communicate to the doctor in case of problems. This system uses temperature, heartbeat,ECG, Saline-level sensor for tracking patient’s health. These sensors are connected to the Arduino-uno. The patient health is tracked with the controller which is in turn interfaced to an LCD display, bluetooth and WI-FI connection to send the data to the web-server (Thinkspeak).In case of any abrupt changes in patient heart-rate or body temperature alert is sent about the patient using IoT. This system also shows patients temperature ,saline level and heartbeat tracked live data with timestamps over the internetwork. Thus, a Patient health monitoring system based on IoT uses the internet to effectively monitor patient health and helps the user monitor themselves.

Survey on Patient Health Monitoring System Based on Internet of Things

Survey on Patient Health Monitoring System Based on Internet of Things

Remote Patient Health Monitoring System

Abstract: With an improvement in technology and miniaturization of sensors, there have been attempts to utilize the new technology in various areas to improve the quality of human life. One main area of research that has seen an adoption of the technology is the healthcare sector. The people in need of healthcare services find it very expensive this is particularly true in developing countries. As a result, this project is an attempt to solve a healthcare problem currently society is facing. The main objective of the project was to design a remote healthcare system. It’s comprised of three main parts. The first part being, detection of patient’s vitals using sensors, second for sending data to database and the last part was providing the detected data for remote viewing. Remote viewing of the data enables a doctor or guardian to monitor a patient’s health progress away from hospital premises. The Internet of Things (IoT) concepts have been widely used to interconnect the available medical resources and offer smart, reliable, and effective healthcare service to the patients. Health monitoring for active and assisted living is one of the paradigms that can use the IoT advantages to improve the patient’s lifestyle. In this project, I have presented an IoT architecture customized for healthcare applications. The aim of the project was to come up with a Remote Health Monitoring System that can be made with locally available sensors with a view to making it affordable if it were to be mass produced. With an improvement in technology and miniaturization of sensors, there have been attempts to utilize the new technology in various areas to improve the quality of human life. One main area of research that has seen an adoption of the technology is the healthcare sector. The people in need of healthcare services find it very expensive this is particularly true in developing countries. Keywords: IoT, MCU, Oxygen Level, Humidity

Internet of Things and Blockchain-Based Framework for Coronavirus (COVID-19) Disease

The COVID-19 is a highly contagious infection which is already had a catastrophic effect on the most serious diseases, including death, around the world. Blockchain-based healthcare systems are being introduced to help simplify mobile and telehealth services, reducing patient stress and the cost of critical clinical services. shared the advantages of blockchain for building a cutting-edge authentication infrastructure and detecting COVID-19 suspicious cases. The authors presented a blockchain-based design for developing a real-time cellular health monitoring system for COVID-19 patients in this paper. This study identifies clinical problems and electronic diagnoses for people with COVID-19 infectious diseases and provides a framework for them. Any mobile application can be configured on digital devices such as smartphones. COVID-19 patients may benefit from such applications. Smartphone apps are designed to save time and money while increasing the efficiency of infectious patients. IoT and Blockchain strategies are presented in the four-layer structure.

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.

Agent-Based Medical Health Monitoring System

One of the leading healthcare concerns worldwide is the aging population. Aged patients require more significant healthcare resources because they are more likely to have chronic diseases that result in higher healthcare expenses. The design and implementation of e-health solutions, which offer patients mobile services to assist and enhance their treatment based on monitoring specific physiological data, is one of the key achievements in medical information technology. In the last few decades, there have been tremendous advancements in healthcare technology regarding mobility, size, speed, and communication. However, the critical drawback of today’s e-Health monitoring systems is that patients are confined to smart rooms and beds with monitoring gadgets. Such tracking is not widespread due to chronic patients’ mobility, privacy, and flexibility issues. Further, health monitoring devices that are fastened to a patient’s body do not give any analysis or advice. To improve the health monitoring process, a multi-agent-based system for health monitoring is provided in this study, which entails a group of intelligent agents that gather patient data, reason together, and propose actions to patients and medical professionals in a mobile context. A multi-agent-based framework presented in this study is evaluated through a case study. The results show that the proposed system provides an efficient health monitoring system for chronic, aged, and remote patients. Further, the proposed approach outperforms the existing mHealth system, allowing for timely health facilities for remote patients using 5G technology.

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

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

Real-time artificial intelligence based health monitoring, diagnosing and environmental control system for COVID-19 patients.

By upgrading medical facilities with internet of things (IoT), early researchers have produced positive results. Isolated COVID-19 patients in remote areas, where patients are not able to approach a doctor for the detection of routine parameters, are now getting feasible. The doctors and families will be able to track the patient's health outside of the hospital utilizing sensors, cloud storage, data transmission, and IoT mobile applications. The main purpose of the proposed research-based project is to develop a remote health surveillance system utilizing local sensors. The proposed system also provides GSM messages, live location, and send email to the doctor during emergency conditions. Based on artificial intelligence (AI), a feedback action is taken in case of the absence of a doctor, where an automatic injection system injects the dose into the patient's body during an emergency. The significant parameters catering to our project are limited to ECG monitoring, SpO2 level detection, body temperature, and pulse rate measurement. Some parameters will be remotely shown to the doctor via the Blynk application in case of any abrupt change in the parameters. If the doctor is not available, the IoT system will send the location to the emergency team and relatives. In severe conditions, an AI-based system will analyze the parameters and injects the dose.

A secure and intelligent real-time health monitoring system for remote cardiac patients

A secure and intelligent real-time health monitoring system for remote cardiac patients

Design a Remote Patient Health Monitoring System (RPHMS) Using IoT

Healthcare has become one of the principal issue with the rise in human population and medical expenditure. For a healthy life, it is essential to follow human body’s vital signals. Continuous Monitoring of patient’s vital signals cannot be provided outside hospital. As it is hard to monitor the patient’s condition for 24 hours, it was proposed in this paper to observe continuously the condition of patient despite the patient being busy with his routine and to screen the health status to the doctors through Internet of Things. This paper proposes health monitoring system using non-intrusive biomedical sensors that measure five parameters like ECG, SPO2, toxic gas, temperature and blood pressure. Proposed method makes use of Arduino Uno Controller to which non-invasive biomedical sensors are connected. The output is displayed on any digital monitoring system using Arduino Uno. The data obtained from the sensors is uploaded to the Thing Speak cloud to store and to access patient’s information by their doctors or by the concerned for necessary follow-ups in real-time. IoT is a powerful domain where sensors can connect and data is viewed over the Internet.

IoT Based Patient Health Monitoring System

Abstract: An IoT based health monitoring system records the patient’s heart beat, body temperature, oxygen levels of blood etc. It can also be used to inform the timing of medication and provides live monitoring of health condition of patient to the doctor available in his chamber. It also sends an SMS alert whenever the health parameter readings go beyond critical values. Keywords: Heart beat, Temperature, Oxygen Levels, Medication timing, SMS alert.

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.

COVID-19 Patient Health Monitoring System

COVID-19 Patient Health Monitoring System