249,621 research outputs found

    Healthcare Monitoring Systems: A WBAN Approach for Patient Monitoring

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    Healthcare Monitoring System, which is expected to reduce healthcare expenses by enabling the continuous monitoring of patient health remotely during their daily activities in healthcare environment. Healthcare applications based on Wireless Sensor Networks are gaining high popularity in all over the world due to their features like flexibility, mobility and ease of constant monitoring of the patient in both outside and inside the body sensed as more useful. The main focus of such system is remote monitoring of patient, inside and outside the hospital room and in ICU in the sense of implantable feature for analysing the patient data. Recent developments in combining sensors, communication systems, and other fields such as cloud computing and Big Data analysis have provided the perfect tools to develop cutting edge systems for improving energy efficiency and consumption with the datasets. Smart homes, smart sensors, and Internet of Things are just a few examples of these application based technologies that will lead to more sustainable and more resilient energy systems. This research work will focus on the Wireless Sensor Networks in terms of emerging wireless technologies which means supporting infrastructure and technology and challenge design issues and as well as security, mobility and energy consumption

    Тhe implementation of mobile health model based on wearable computing

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    Предмет истраживања дисертације је развој модела мобилног здравства заснованог на wearable computing-у. Централни проблем који се разматра у докторској дисертацији је испитивање могућности примене и интеграције wearable computing-а, Интернета интелигентних уређаја (енг. Internet of Things, IoT), мобилних технологија и сервиса, big data аналитике и рачунарства у облаку за развој сервиса мобилног здравства. Фокус истраживања биће на примени сервиса мобилног здравства у области мерења, праћења и контроле стреса код студената. Увођењем Интернета интелигентних уређаја у мобилно здравство, у области контроле стреса, омогућава се прикупљање података са тела корисника путем сензора. Примена wearable уређаја у процесу контроле стреса лекарима или психолозима треба да омогући добијање информација о психофизичком стању корисника. Применом сервиса електронског здравства измерени подаци се прате, чувају и врши се анализа података. На основу аналитичких резултата могу сe креирати одговарајуће методе за контролу стреса и персонализоване превентивне здравствене поруке намењене корисницима. Предложен је модел мобилног здравства заснован на wearable computing-у који се састоји из система мобилног здравства, wearable система и сервиса за међусобну интеграцију компоненти и интеграцију са електронским здравством. Осим тога, модел обухвата интеграцију мобилног здравства са програмима формалног образовања. У екперименталном делу докторске дисертације предложени модел мобилног здравства заснован на wearable computing-у је имплементиран у образовном окружењу. Систем је евалуиран у реалном окружењу, током одбране завршних радова студената на Факултету организационих наука Универзитета у Београду. Резултати су показали да је коришћење мобилне апликације са садржајима за релаксацију утицало на смањење стреса код студената током одбране завршних радова.The subject of this thesis is development of mobile health model based on wearable computing. The main problem discussed in the thesis is to investigate the possibilities of implementation and integration of wearable computing, Internet of Things, mobile technologies and services, big data analytics, and Cloud computing for the development of mobile health services. By introducing the Internet of Things into mobile healthcare, in the field of stress control, it is possible to collect sensors’ data from the users’ body. The use of the wearable devices in the process of the stress control by physicians or psychologists should enable obtaining information on the psychophysical condition of the user. The measured data could be monitored, stored and analyzed using the e-health services. Appropriate methods for controlling stress and personalized preventive health messages for users can be created based on analytical results. The thesis proposes a mobile healthcare model based on wearable computing. It consists of a mobile healthcare system, wearable systems and services for interconnection of components and integration with electronic health services. In addition, the model includes the integration of mobile healthcare and formal education programs. In the experimental part of the thesis, the proposed model of mobile healthcare based on wearable computing has been implemented in an educational environment. The system was evaluated in a real environment, during the defense of students' thesis at the Faculty of Organizational Sciences, University of Belgrade. The results show that the use of a mobile application with relaxation content affected the reduction of stress among students during their thesis defense. In addition, this thesis outlines the role of the education system in the implementation of mobile healthcare. The approach to designing a course for smart healthcare engineers has been presented. Through key topics of the course, students should gain new skills and knowledge of smart healthcare based modern technologies. The proposed approach was evaluated at the Faculty of Organizational Sciences, University of Belgrade. The results point to the positive outcome of the process of acquiring knowledge, as well as the students' experiences and attitudes about the course

    An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments

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    The new Internet of Things paradigm allows for small devices with sensing, processing and communication capabilities to be designed, which enable the development of sensors, embedded devices and other ‘things’ ready to understand the environment. In this paper, a distributed framework based on the internet of things paradigm is proposed for monitoring human biomedical signals in activities involving physical exertion. The main advantages and novelties of the proposed system is the flexibility in computing the health application by using resources from available devices inside the body area network of the user. This proposed framework can be applied to other mobile environments, especially those where intensive data acquisition and high processing needs take place. Finally, we present a case study in order to validate our proposal that consists in monitoring footballers’ heart rates during a football match. The real-time data acquired by these devices presents a clear social objective of being able to predict not only situations of sudden death but also possible injuries.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness (MINECO/FEDER) under the granted Project SEQUOIA-UA (Management requirements and methodology for Big Data analytics) TIN2015-63502-C3-3-R, by the University of Alicante, within the program of support for research, under project GRE14-10, and by the Conselleria de Educación, Investigación, Cultura y Deporte, Comunidad Valenciana, Spain, within the program of support for research, under project GV/2016/087. This work has also been partially funded by Vicerrectorado de Innovación, University of Alicante, Spain (Vigrob)

    Medical data processing and analysis for remote health and activities monitoring

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    Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

    How 5G wireless (and concomitant technologies) will revolutionize healthcare?

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    The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution
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