INTEGRATION OF INTERNET OF THINGS AND HEALTH RECOMMENDER SYSTEMS

The Internet of Things (IoT) has become a part of our lives and has provided many enhancements to day-to-day living. In this project, IoT in healthcare is reviewed. IoT-based healthcare is utilized in remote health monitoring, observing chronic diseases, individual fitness programs, helping the elderly, and many other healthcare fields. There are three main architectures of smart IoT healthcare: Three-Layer Architecture, Service-Oriented Based Architecture (SoA), and The Middleware-Based IoT Architecture. Depending on the required services, different IoT architecture are being used. In addition, IoT healthcare services, IoT healthcare service enablers, IoT healthcare applications, and IoT healthcare services focusing on Smartwatch are presented in this research. Along with IoT in smart healthcare, Health Recommender Systems integration with IoT is important. Main Recommender Systems including Content-based filtering, Collaborative-based filtering, Knowledge-based filtering, and Hybrid filtering with machine learning algorithms are described for the Health Recommender Systems. In this study, a framework is presented for the IoT-based Health Recommender Systems. Also, a case is investigated on how different algorithms can be used for Recommender Systems and their accuracy levels are presented. Such a framework can help with the health issues, for example, risk of going to see the doctor during pandemic, taking quick actions in any health emergencies, affordability of healthcare services, and enhancing the personal lifestyle using recommendations in non-critical conditions. The proposed framework can necessitate further development of IoT-based Health Recommender Systems so that people can mitigate their medical emergencies and live a healthy life

Mobile Health Technologies

Mobile Health Technologies, also known as mHealth technologies, have emerged, amongst healthcare providers, as the ultimate Technologies-of-Choice for the 21st century in delivering not only transformative change in healthcare delivery, but also critical health information to different communities of practice in integrated healthcare information systems. mHealth technologies nurture seamless platforms and pragmatic tools for managing pertinent health information across the continuum of different healthcare providers. mHealth technologies commonly utilize mobile medical devices, monitoring and wireless devices, and/or telemedicine in healthcare delivery and health research. Today, mHealth technologies provide opportunities to record and monitor conditions of patients with chronic diseases such as asthma, Chronic Obstructive Pulmonary Diseases (COPD) and diabetes mellitus. The intent of this book is to enlighten readers about the theories and applications of mHealth technologies in the healthcare domain

Trustworthy Wireless Personal Area Networks

In the Internet of Things (IoT), everyday objects are equipped with the ability to compute and communicate. These smart things have invaded the lives of everyday people, being constantly carried or worn on our bodies, and entering into our homes, our healthcare, and beyond. This has given rise to wireless networks of smart, connected, always-on, personal things that are constantly around us, and have unfettered access to our most personal data as well as all of the other devices that we own and encounter throughout our day. It should, therefore, come as no surprise that our personal devices and data are frequent targets of ever-present threats. Securing these devices and networks, however, is challenging. In this dissertation, we outline three critical problems in the context of Wireless Personal Area Networks (WPANs) and present our solutions to these problems. First, I present our Trusted I/O solution (BASTION-SGX) for protecting sensitive user data transferred between wirelessly connected (Bluetooth) devices. This work shows how in-transit data can be protected from privileged threats, such as a compromised OS, on commodity systems. I present insights into the Bluetooth architecture, Intel’s Software Guard Extensions (SGX), and how a Trusted I/O solution can be engineered on commodity devices equipped with SGX. Second, I present our work on AMULET and how we successfully built a wearable health hub that can run multiple health applications, provide strong security properties, and operate on a single charge for weeks or even months at a time. I present the design and evaluation of our highly efficient event-driven programming model, the design of our low-power operating system, and developer tools for profiling ultra-low-power applications at compile time. Third, I present a new approach (VIA) that helps devices at the center of WPANs (e.g., smartphones) to verify the authenticity of interactions with other devices. This work builds on past work in anomaly detection techniques and shows how these techniques can be applied to Bluetooth network traffic. Specifically, we show how to create normality models based on fine- and course-grained insights from network traffic, which can be used to verify the authenticity of future interactions

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

Distributed Computing and Monitoring Technologies for Older Patients

This book summarizes various approaches for the automatic detection of health threats to older patients at home living alone. The text begins by briefly describing those who would most benefit from healthcare supervision. The book then summarizes possible scenarios for monitoring an older patient at home, deriving the common functional requirements for monitoring technology. Next, the work identifies the state of the art of technological monitoring approaches that are practically applicable to geriatric patients. A survey is presented on a range of such interdisciplinary fields as smart homes, telemonitoring, ambient intelligence, ambient assisted living, gerontechnology, and aging-in-place technology. The book discusses relevant experimental studies, highlighting the application of sensor fusion, signal processing and machine learning techniques. Finally, the text discusses future challenges, offering a number of suggestions for further research directions

Strategic Intelligence Monitor on Personal Health Systems (SIMPHS): Report on Typology/Segmentation of the PHS Market

This market segmentation reports for Personal Health Systems (PHS) describes the methodological background and illustrates the principles of classification and typology regarding different fragments forming this market. It discusses different aspects of the market for PHS and highlights challenges towards a stringent and clear-cut typology or defining market segmentation. Based on these findings a preliminary hybrid typology and indications and insights are created in order to be used in the continuation of the SIMPHS project. It concludes with an annex containing examples and cases studies.JRC.DDG.J.4-Information Societ

M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

Mobile devices in applications for healthcare: systems and technology

Actualmente, la evolución de las comunicaciones inalámbricas y de las tecnologías de red permite el acceso a servicios médicos de manera remota desde una gran variedad de dispositivos móviles. Este nuevo contexto técnico-sanitario se conoce como m-Health y, junto con otras tendencias de nueva aparición sector como el historial clínico electrónico (HCE), podría suponer una auténtica revolución en el sector de la salud y, más concretamente, en el tratamiento y seguimiento de enfermedades crónicas. En este proyecto se exploran las posibilidades ofrecidas por e-Health y, más detalladamente, por m-Health para la gestión de enfermedades crónicas por parte del propio paciente desde un punto de vista técnico, haciendo especial hincapié en la estructura de comunicaciones necesaria. Para ello, se describen las tecnologías, arquitecturas y dispositivos disponibles con capacidad suficiente para satisfacer los requisitos establecidos por una enfermedad crónica concreta: diabetes. Atendiendo a estas consideraciones, se propone un sistema para el tratamiento de la diabetes basado en las oportunidades de las tecnologías inalámbricas actuales. Por último, el texto concluye con una serie de observaciones sobre la situación actual de m-Health y sus futuros retos.At present, the evolution of wireless communications and networking technologies allows the access to medical services from a great variety of mobile devices remotely. This new technicalmedical context is known as m-Health and, along with other emerging health trends like electronic health record (EHR), could be a revolution in the health sector and, more specifically, in the treatment and monitoring of chronic diseases. This project will explore the possibilities offered by e-Health and, in more detail, by m-Health for the self-management of chronic diseases from a technical point of view, with particular emphasis on the necessary communications structure. To do so, we describe the technologies, architectures and devices available with sufficient capacity to meet the requirements of specific chronic disease: diabetes. In response to these considerations, we propose a system for the treatment of diabetes based on current wireless technologies opportunities. Finally, the text concludes with a series of observations on the current status of m-Health and its future challenges.Ingeniería de TelecomunicaciónTelekomunikazio Ingeniaritz

The effect of interrupting sedentary behaviour on the cardiometabolic health of adults with sedentary occupations

A dissertation submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Medicine Johannesburg, 2018.There has been an increase in the percentage of individuals employed in sedentary occupations over the last 50 years. Prolonged sedentary time has been associated with poorer cardiometabolic health. Interrupting prolonged sedentary activity may attenuate the risk of developing cardiometabolic disease. This study aimed to determine whether prompts delivered via a mobile phone were effective in reducing sedentary behaviour (measured objectively using an Actigraph and activPAL accelerometer) in people with sedentary occupations. Twenty men and women were randomly assigned to either a control or intervention (PROMPT) group. Only participants in the PROMPT group were instructed to interrupt their sedentary behaviour. During the intervention participants in the PROMPT group spent less time in sedentary behaviour (5.5±0.5 hrs/day) during their working day, compared to the control group (6.7±0.6 hrs/day) as measured using the activPAL (p=0.04). There was no association between the intervention and cardiometabolic health variables. There were differences in the outputs of ActiGraph and activPAL accelerometers. Interrupting prolonged sedentary time via mobile phone messages may be an effective strategy in reducing total sedentary time in the workplace.LG201