967 research outputs found
Investigation of Secure Health Monitoring System Using IOT
The rapid progress of technology, particularly the Internet of Things (IoT), has introduced exciting opportunities for transforming the healthcare sector. One significant area where IoT has made a significant impact is in the creation of secure health monitoring systems. These systems utilize IoT devices and sensors to gather and transmit live health data, facilitating remote monitoring and individualized healthcare.The integration of IoT in healthcare monitoring offers numerous benefits, including improved patient outcomes, enhanced access to care, and increased efficiency in healthcare delivery.To develop you would typically follow a research methodology that involves several key steps. Clearly state the objectives of your research, such as designing and implementing a secure health monitoring system using IoT. Specify the aspects you want to focus on, such as data privacy, authentication, encryption, or device communication. Develop a high-level system architecture for your health monitoring system. Define the components, their functionalities, and how they interact with each other. Consider the security aspects, such as secure data transmission, authentication, access control, and data storage.By multiplying each of our goals by a weight provided by the user, we can scale our collection of goals into a single goal using the weighted sum approach. One of the most popular strategies is this one. Finding the appropriate weights to give each aim while using the weighted sum approach is a concern. Taken as alternative parameters for HMS1, HMS2, HMS3, HMS4, HMS5. Taken as evaluation parameters for Portability,Round-The-Clock Health Surveillance,ease of use,Reliability.HMS1 performance is good when compared to others so HMS 1 is preferred except HMS 1 performed better in secure health monitoring system using IIOD
Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges
Chronic diseases are becoming more widespread. Treatment and monitoring of these diseases require going to hospitals frequently, which increases the burdens of hospitals and patients. Presently, advancements in wearable sensors and communication protocol contribute to enriching the healthcare system in a way that will reshape healthcare services shortly. Remote patient monitoring (RPM) is the foremost of these advancements. RPM systems are based on the collection of patient vital signs extracted using invasive and noninvasive techniques, then sending them in real-time to physicians. These data may help physicians in taking the right decision at the right time. The main objective of this paper is to outline research directions on remote patient monitoring, explain the role of AI in building RPM systems, make an overview of the state of the art of RPM, its advantages, its challenges, and its probable future directions. For studying the literature, five databases have been chosen (i.e., science direct, IEEE-Explore, Springer, PubMed, and science.gov). We followed the (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) PRISMA, which is a standard methodology for systematic reviews and meta-analyses. A total of 56 articles are reviewed based on the combination of a set of selected search terms including RPM, data mining, clinical decision support system, electronic health record, cloud computing, internet of things, and wireless body area network. The result of this study approved the effectiveness of RPM in improving healthcare delivery, increase diagnosis speed, and reduce costs. To this end, we also present the chronic disease monitoring system as a case study to provide enhanced solutions for RPMsThis research work was partially supported by the Sejong University Research Faculty Program (20212023)S
A cyber-physical system for smart healthcare
Abstract: The increasing number of patients in hospitals is becoming a serious concern in most countries owing to the significantly associated implications for resources such as staff and budget shortages. This problem has prompted researchers to investigate low-cost alternative systems that may assist medical staff with monitoring and caring for patients. In view of the recent widespread availability of cost-effective internet of things (IoT) technologies such as ZigBee, WiFi and sensors integrated into cyber-physical systems, there is the potential for deployment as different topologies in applications such as patient diagnoses and remote patient monitoring...M.Tech. (Electrical and Electronic Engineering Technology
Improving Access and Mental Health for Youth Through Virtual Models of Care
The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial
The Impact of Digital Technologies on Public Health in Developed and Developing Countries
This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic
A Fuzzy Logic Architecture for Rehabilitation Robotic Systems
Robots are highly incorporated in rehabilitation in the last decade to compensate lost functions in disabled individuals. By controlling the rehabilitation robots from far, many benefits are achieved. These benefits include but not restricted to minimum hospital stays, decreasing cost, and increasing the level of care. The main goal of this work is to have an effective solution to take care of patients from far. Tackling the problem of the remote control of rehabilitation robots is undergoing and highly challenging. In this paper, a remote wrist rehabilitation system is presented. The developed system is a sophisticated robot ensuring the two wrist movements (Flexion /extension and abduction/adduction). Additionally, the proposed system provides a software interface enabling the physiotherapists to control the rehabilitation process remotely. The patient’s safety during the therapy is achieved through the integration of a fuzzy controller in the system control architecture. The fuzzy controller is employed to control the robot action according to the pain felt by the patient. By using fuzzy logic approach, the system can adapt effectively according to the patients’ conditions. The Queue Telemetry Transport Protocol (MQTT) is considered to overcome the latency during the human robot interaction. Based on a Kinect camera, the control technique is made gestural. The physiotherapist gestures are detected and transmitted to the software interface to be processed and be sent to the robot. The acquired measurements are recorded in a database that can be used later to monitor patient progress during the treatment protocol. The obtained experimental results show the effectiveness of the developed remote rehabilitation system
Innovative Business Model for Smart Healthcare Insurance
Information revolution and technology growth have made a considerable contribution to restraining the cost expansion and empowering the customer. They disrupted most business models in different industries. The customer-centric business model has pervaded the different sectors. Smart healthcare has made an enormous shift in patient life and raised their expectations of healthcare services quality. Healthcare insurance is an essential business in the healthcare sector; patients expect a new business model to meet their needs and enhance their wellness. This research develops a holistic smart healthcare architecture based on the recent development of information and communications technology. Then develops a disruptive healthcare insurance business model that adapts to this architecture and classifies the patient according to their technology needs. Finally, and implementing a prototype of a system that matches and suits the healthcare recipient condition to the proper healthcare insurance policy by applying Web Ontology Language (OWL) and rule-based reasoning model using SWRL using Protég
Aproximação inteligente baseada no design de sistemas integrados para aplicativos de telemedicina
Introduction: The present research was conducted at Sikha ‘O’ Anusandan (deemed to be University) in 2017. Telemedicine application in the field of medicine creates a new age. Accordingly, it requires technology to be compatible. Easy access and fast processing are the major focuses in different applications. In this paper, an approach has been considered to diagnose heart diseases.
Methods: The model is designed using fuzzy logic in which the rule-based principle is applied to satisfy the objective. The model is developed keeping a view over the multi-agent system. The diagnosis of the patient is performed using Fuzzy Inference System (fis).
Results: The pathological test results will help to form the rules of the model and can work for the diagnosis in a convenient way. Furthermore, the results of detection are communicated through Internet and sms for monitoring and post care purpose of supporting IoT application.
Conclusion: The simulated result shows its performance can be helpful to physicians as well as patients from remote places.
Originality: The model is proposed for disease detection and monitoring patients on remote locations. Also, distributed agents are proposed to act on a common platform using Internet for the benefit of society. This will save time for physicians and travelling costs for the patient.
Limitations: The research results can be practically implemented in new medical equipment for hospitals with earlier equipment.Introducción: la presente investigación se realizó en Sikha ‘O’ Anusandan (la cual se considera una universidad) en 2017. La aplicación de la telemedicina en el campo de la medicina genera una nueva era. En consecuencia, requiere que la tecnologÃa sea compatible. Las caracterÃsticas principales que se demandan de dichas aplicaciones son el fácil acceso y el procesamiento rápido. Este estudio se aproxima a la telemedicina para el caso de diagnosis de enfermedades cardÃacas.
Métodos: el modelo se diseña mediante una lógica difusa en la que se aplica el principio basado en reglas para satisfacer el objetivo. El modelo se desarrolla teniendo en cuenta el sistema de agentes múltiples. El diagnóstico del paciente se realiza con el sistema de inferencia difusa (fis).
Resultados: los resultados de la prueba patológica ayudarán a formar las reglas del modelo y pueden aportar para el diagnóstico de manera conveniente. Además, los resultados de la detección se comunican a través de Internet y sms para fines de seguimiento y cuidado posterior de la aplicación IoT.
Conclusión: el resultado simulado muestra que su desempeño puede ser útil tanto para médicos como para pacientes en lugares remotos.
Originalidad: se propone el modelo para detectar enfermedades y monitorear pacientes situados en locaciones remotas. Además, se propone que agentes distribuidos en una zona actúen sobre una plataforma común utilizando internet para el beneficio de la sociedad, esto ahorrará tiempo a los médicos y costos de traslado o transporte del paciente.
Limitaciones: los resultados de la investigación se pueden implementar de forma práctica en nuevos equipos médicos para hospitales con equipos ya existentes.Introdução: a presente pesquisa foi realizada na Universidade de Sikha ‘O’ Anusandan, em 2017. O aplicativo de telemedicina no campo da medicina gera uma nova era. Em consequência, requer que a tecnologia seja compatÃvel. O acesso fácil e o processamento rápido são as principais caracterÃsticas esperadas dos diferentes aplicativos. Neste estudo foi considerada uma aproximação para diagnosticar as doenças cardÃacas.Métodos: o design do modelo é feito através de uma lógica difusa, na qual o princÃpio baseado em regras para satisfazer o objetivo é utilizado. O modelo é desenvolvido tendo em conta o sistema de agentes múltiplos. O diagnóstico do paciente é realizado utilizando o sistema de inferência difusa (fis).Resultados: os resultados do exame patológico ajudarão a formar as regras do modelo e podem contribuir para o diagnóstico de forma conveniente. Além disso, os resultados do exame são comunicados, por internet e sms, para fins de seguimento e cuidado posterior do aplicativo IoT.Conclusão: o resultado simulado mostra que seu desempenho pode ser útil tanto para médicos quanto para pacientes em lugares remotos.Originalidade: é proposto o modelo para detectar doenças e monitorar pacientes situados em lugares remotos. Além disso, é proposto que agentes distribuÃdos em determinadas zonas utilizem uma plataforma comum, fazendo uso da internet para beneficiar a sociedade, o que economizará tempo para os médicos e custos de traslado e/ou transporte do paciente.Limitações: os resultados da pesquisa podem ser inseridos de forma prática em novas equipes médicas para hospitais com equipes já existentes
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