ABSTRACT
Ever since an anonymous disease broke out in late 2019, the whole world seems to have own ceased functioning. COVID-19 patients are proliferating at an exponential rate, straining healthcare systems around the world. Traditional techniques of screening every patient with a respiratory disease is unfeasible due to the restricted number of testing kits available. We presented a method for recognizing COVID-19 infected patients utilizing data collected from chest X-ray scans to overcome this challenge. This attempt will benefit both patients and doctors significantly. It becomes even more critical in nations where the number of people affected far outnumbers the number of laboratory kits available to test the disease. When current systems are confused whether to retain the patient on the ward with other patients or isolate them in COVID-19 zones, this could be useful in an inpatient setting. Apart from that, it would aid in the identification of patients with a high risk of COVID-19 and a false negative RT-PCR who would require a repeat. Most of the COVID-19 detection methods use traditional image classification models. This has the issue of low detection accuracy and incorrect COVID-19 detection. This method starts with a chest x-ray enhancement procedure like this: Rotation, translation, random conversion. The survey's accuracy has considerably increased as a result of this. For the COVID-19 infection, our model has 97.5 percent accuracy and 100 percent sensitivity (recall). In addition, we used a visualization technique that distinguishes our model from the others by displaying contaminated areas in X-ray pictures. © 2022 IEEE.
ABSTRACT
This paper presents a systematic review of android app respiratory system on smartphone. For some diseases, doctors have succeeded in inventing the necessary treatments that lasts for a short period, but in several cases, the treatment can stay for a lifetime. The goal of this system is to detect if a patient has any respiratory disease(s) by specifying the symptoms the patient encounters, schedules an appointement in the hospital for patient through the system to the linked specialist doctors to avoid contact in the case of Covid-19 patient. This research will help raise patient's awareness of the high risk of late discovery of having respiratory diseases (like Lung Cancer. corona virus etc), and also to develop a model that will help detect this disease early through mobile application. The focus of this review is to encourage medical institutions to adopt the health android app that can help patients in self-managing behavioral activities such as physical activities, using symptoms to determine the stage(early or critical) of the disease and drug suggestions with research evaluation using the app, this could help patients monitor and manage their health conditions. © 2022 IEEE.
ABSTRACT
Some diseases today have a rapid and dangerous rate of transmission. This causes doctors or medical personnel have a high risk of transmission. It caused the need for a system that can monitor the patient's condition in order to minimize the risk of contacting medical personnel. The research aims to design and build an integrated IoT-based patient monitoring system that provided information about the patient's temperature, infusion fluid level, and heart rate. This system is equipped with a database of patient conditions and can be accessed by web-based users. This system is integrated between hardware, software, and IoT system, which allows users to access data (based on their respective roles) from various places, because they can access it via the internet. The research stages are hardware and software design, design implementation, software embedded system development, IoT design, system integration, and web development that is integrated with IoT. The system has been running well and patient's information can be accessed by the user. This system is also equipped with indicators of normal and abnormal conditions, so that medical personnel can anticipate early if there are conditions that are dangerous for patients. Even though Covid cases have decreased, technology is still needed, especially to be used to monitor the condition of patients who require intensive monitoring. © 2022 IEEE.
ABSTRACT
Medical specialists are primarily interested in researching health care as a potential replacement for conventional healthcare methods nowadays. COVID-19 creates chaos in society regardless of the modern technological evaluation involved in this sector. Due to inadequate medical care and timely, accurate prognoses, many unexpected fatalities occur. As medical applications have expanded in their reaches along with their technical revolution, therefore patient monitoring systems are getting more popular among the medical actors. The Internet of Things (IoT) has met the requirements for the solution to deliver such a vast service globally at any time and in any location. The suggested model shows a wearable sensor node that the patients will wear. Monitoring client metrics like blood pressure, heart rate, temperature, etc., is the responsibility of the sensor nodes, which send the data to the cloud via an intermediary node. The sensor-acquired data are stored in the cloud storage for detailed analysis. Further, the stored data will be normalized and processed across various predictive models. Among the different cloud-based predictive models now being used, the model having the highest accuracy will be treated as the resultant model. This resultant model will be further used for the data dissemination mechanism by which the concerned medical actors will be provided an alert message for a proper medication in a desirable manner. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
People have struggled with many infectious diseases throughout history. Today, the Covid-19 is being fought. One of the most important things for people who have or are at risk of getting Covid-19 is social isolation. Many countries resort to different ways to ensure social isolation. For this, remote patient monitoring systems have been developed. In this study, the problem of the selection of Covid-19 remote patient monitoring systems is discussed. Seven Wearable Health Technology (WHT) products were evaluated with a total of 10 criteria, including the important symptoms used in the patient tracking systems. The weights of 10 criteria determined by the Analytical Hierarchy Process (AHP) method were calculated, and these weights were used in the solution of The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), and Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) methods. WHT products were compared. As a result, the most appropriate patient follow-up system was determined. This study generates differences in terms of evaluating seven different products and ten criteria in total with MCDM methods. A more comprehensive evaluation has been made in the literature than the studies in this field. © 2022, The Author(s).
ABSTRACT
In recent years, internet of things (IoT) technology has shown great potential in the health care sector through different wearable sensors. Monitoring various health parameters like body temperature, blood pressure, heartbeat, oxygen level, and sugar level is very important for being proactive against chronic and pandemic diseases. Monitoring patients is a great challenge during pandemic diseases since doctors and other medical practitioners are exposed to risk. This paper presents a novel touchless health and patient monitoring system embedding ultra-wideband (UWB) and IoT technolo-gies for effective monitoring of COVID-19 patients. The IoT module is specifically designed for health monitoring whereas UWB radar is designated for effective touchless patient monitoring. The IoT module comprises a temperature sensor, heartbeat sensor, and pulse oximeter, which sense and store the information in the Internet cloud, which can then be accessed through mobile and web applications. UWB radar is integrated with the system for touchless patient monitoring. The proposed system is also embedded with a heath-assisting module that allows patients to interact with doctors after receiving their health parameters through the mobile bot application termed IOT FIT BOT. A mobile application and a web-based graphical user interface are developed to receive sensed data immediately. Thus the proposed system provides effective health monitoring along with live health assistance, and more importantly, the system offers touchless patient monitoring, which will be a promising solution for medical professionals during pandemic situations like COVID-19. © 2022 by Begell House, Inc.
ABSTRACT
The Coronavirus outbreak has become massive in recent years. World Health organization warned about the COVID-19 pandemic in March 2020. The United States' Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) kept tracking the pandemic effects and provided information on their websites. One such application is in healthcare, where COVID-19 patient health is tracked. The Internet of Things (IoT) increases medical equipment efficiency by allowing for practical tracking of health of affected patients, with wearable devices collecting information and reducing possible errors by humans. The collected details of a patient are transferred via a gateway from medical equipment to the Internet of Things, where they are stored and reviewed. One of the greatest roadblocks to the adoption of the could computing for medical applications is the tracking of each and every affected people from multiple places. Therefore, cloud computing in IoT offers a significant remedy for tracking people at minimum cost and improved disease treatment in the medical industry. The patient's body temperature and respiration are monitored. © 2022 IEEE.
ABSTRACT
Recent technological advancements have opened the path for smart gadgets, including wearable devices. Wearable sensors can predict human body motions and track a variety of medical symptoms associated with chronic diseases. The proposed study utilizes IoT sensors to monitor human bodily states, with the obtained data being saved in a cloud context. The data saved in the cloud environment is analyzed further using data analysis algorithms to enable clinicians' efficient monitoring and prompt response. Moreover, data fluctuation may assist physicians in notifying them of emergencies, preserving a precious human life. The proposal might be implemented efficiently in emergency medical settings when patients need continual monitoring and the greatest attention from medical professionals. The suggested idea might be used to deploy several life-threatening conditions such as spinal muscular atrophy, hypertrophic cardiomyopathy, and Covid patient monitoring. © 2022 IEEE.
ABSTRACT
Social distancing, isolation, and quarantining are very familiar words since the outbreak of the coronavirus (COVID-19). COVID - 19 is a highly contagious pathogenic viral infection. It is very risky to get close contact with people who have COVID-19 symptoms or COVID-19 positive;nevertheless, covid patient monitoring is also significant for saving his/her life. To solve the Covid-19 pandemic situation accentuates a focus on remote patient monitoring. A small smart healthcare support system is built to monitor COVID-19 patients' health status and the patient emergency abet. This system can also trace the patient location;thus, aid can be provided to the patient promptly. This system uses a respiration sensor, oxygen saturation sensor, temperature sensor, heart rate sensor, GPS. All the sensors, as well as GPS, are connected with Arduino-Uno. By processing sensor data, the smart system can discern the patient's critical condition and forward this information to the doctor/nurse or hospital in charge and patient relative's smartphone as a text message. This paper aims to develop a system to support COVID-19 patients and develop a remote healthcare platform for monitoring pandemic situations and providing emergency aid promptly as a text to the smartphone. © 2021 IEEE.
ABSTRACT
COVID-19 is a global pandemic afflicting our society. We propose covIoT, a novel Arduino-based automatic hand sanitizer dispenser, integrated with an oximeter, a heart rate monitor, a non-contact body temperature sensor, and voice assistant feedback. This system can be deployed as an end-to-end COVID patient monitoring system and also for automated sanitization. The system was tested on 100 people to evaluate its performance. The mean absolute error and root mean square error values were found to be 0.79 and 1.03 for the oximeter, 1.22 and 0.70 for the heart rate monitor and 1.07 and 1.28 for the body temperature monitor, respectively, compared to the industry-standard devices. These low error values indicate the high accuracy of our proposed system. We believe this is the first low-cost integrated patient monitoring and sanitization system with vocal feedback, to increase accessibility and ultimately helps combat the virus. © 2022 IEEE.
ABSTRACT
The Covid-19 Pandemic has affected the entire world. Most notably, the healthcare industry has been under constant pressure to treat patients. Spikes in the number of patients have put the workforce under tremendous pressure. Doctors and nurses are finding it difficult to observe multiple patients at the same time. In addition to that, medical practitioners are reluctant to deal with the diagnosis and treatments, as it requires frequent physical intervention. The aim of this project is to reduce this strain on medical practitioners by developing a system that aims to constantly track the activity of the patients and replicate the same using a 3D Human Model. For this multiple Inertial Motion Sensors (IMU's) are used that will collect the motion data of the joints of the patient, with help of which our 3D Model will replicate the actions. The system will use Internet of Things and Cloud Computing to collect and transfer data to the web application. All the activity of the patient can be monitored using fully authenticated web applications by doctors and even by the family members. Thus with the help of the technology patients can be monitored without any physical intervention and the risk of getting affected by viruses or diseases for the doctors is also minimized. © 2022 IEEE.