Smart Healthcare: A guide to Understand Context-Awareness in Healthcare

Pervasive healthcare is the conceptual system of providing healthcare to anyone, at anytime, and anywhere by removing restraints of time and location while increasing both the coverage and the quality of healthcare. Pervasive Healthcare Computing is at the forefront of this research, and presents the ways in which mobile and wireless technologies can be used to implement the vision of pervasive healthcare. This vision includes prevention, healthcare maintenance and checkups; short-term monitoring (home healthcare), long-term monitoring (nursing home), and personalized healthcare monitoring; and incidence detection and management, emergency intervention, transportation and treatment. The pervasive healthcare applications include intelligent emergency management system, pervasive healthcare data access, and ubiquitous mobile telemedicine. Pervasive Healthcare Computing includes the treatment of several new wireless technologies and the ways in which they will implement the vision of pervasive healthcare.

Individuals with disabilities often have difficulty accomplishing tasks, living independently, and utilizing information technologies; simple aspects of daily life taken for granted by non-disabled individuals. Assistive Technologies: Concepts, Methodologies, Tools, and Applications presents a comprehensive collection of research, developments, and knowledge on technologies that enable disabled individuals to function effectively and accomplish otherwise impossible tasks. These volumes serve as a crucial reference source for experts in fields as diverse as healthcare, information science, education, engineering, and human-computer interaction, with applications bridging multiple disciplines.

The use of contextually aware, pervasive, distributed computing, and sensor networks to bridge the gap between the physical and online worlds is the basis of mobile social networking. This book shows how applications can be built to provide mobile social networking, the research issues that need to be solved to enable this vision, and how mobile social networking can be used to provide computational intelligence that will improve daily life. With contributions from the fields of sociology, computer science, human-computer interaction and design, this book demonstrates how mobile social networks can be inferred from users' physical interactions both with the environment and with others, as well as how users behave around them and how their behavior differs on mobile vs. traditional online social networks.

Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Applications of Artificial Intelligence reviews the research, focusing on state-of-the-art projects in the field. The book captures the breadth and depth of the medical applications of artificial intelligence, exploring new developments and persistent challenges.

This two-volume set LNCS 11581 and 11582 constitutes the thoroughly refereed proceedings of the 10th International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, DHM 2019, which was held as part of the 21st HCI International Conference, HCII 2019, in Orlando, FL, USA, in July 2019. The total of 1275 papers and 209 posters included in the 35 HCII 2019 proceedings volumes were carefully reviewed and selected from 5029 submissions. DHM 2019 includes a total of 77 papers; they were organized in topical sections named: Part I, Human Body and Motion: Anthropometry and computer aided ergonomics; motion prediction and motion capture; work modelling and industrial applications; risk assessment and safety. Part II, Healthcare Applications: Models in healthcare; quality of life technologies; health dialogues; health games and social communities.

Ambient intelligence (AmI) is an element of pervasive computing that brings smartness to living and business environments to make them more sensitive, adaptive, autonomous and personalized to human needs. It refers to intelligent interfaces that recognise human presence and preferences, and adjust smart environments to suit their immediate needs and requirements. The key factor is the presence of intelligence and decision-making capabilities in IoT environments. The underlying technologies include pervasive computing, ubiquitous communication, seamless connectivity of smart devices, sensor networks, artificial intelligence (AI), machine learning (ML) and context-aware human-computer interaction (HCI). AmI applications and scenarios include smart homes, autonomous self-driving vehicles, healthcare systems, smart roads, the industry sector, smart facilities management, the education sector, emergency services, and many more. The advantages of AmI in the IoT environment are extensive. However, as for any new technological paradigm, there are also many open issues and limitations. This book discusses the AmI element of the IoT and the relevant principles, frameworks, and technologies in particular, as well as the benefits and inherent limitations. It reviews the state of the art of current developments relating to smart spaces and AmI-based IoT environments. Written by leading international researchers and practitioners, the majority of the contributions focus on device connectivity, pervasive computing and context modelling (including communication, security, interoperability, scalability, and adaptability). The book presents cutting-edge research, current trends, and case studies, as well as suggestions to further our understanding and the development and enhancement of the AmI-IoT vision.

The two-volume set LNCS 10896 and 10897 constitutes the refereed proceedings of the 16th International Conference on Computers Helping People with Special Needs, ICCHP 2018, held in Linz, Austria, in July2018. The 101 revised full papers and 78 short papers presented were carefully reviewed and selected from 356 submissions. The papers are organized in the following topical sections: Web accessibility in the connected world; accessibility and usability of mobile platforms for people with disabilities and elderly persons: design, development and engineering; accessible system/information/document design; accessible e-learning - e-learning for accessibility/AT; personalized access to TV, film, theatre, and music; digital games accessibility; accessibility and usability of self-service terminals, technologies and systems; universal learning design; motor and mobility disabilities: AT, HCI, care; empowerment of people with cognitive disabilities using digital technologies; augmented and alternative communication (AAC), supported speech; Art Karshmer lectures in access to mathematics, science and engineering; environmental sensing technologies for visual impairment; 3D printing in the domain of assistive technologies (AT) and do it yourselves (DIY) AT; tactile graphics and models for blind people and recognition of shapes by touch; access to artworks and its mediation by and for visually impaired people; digital navigation for people with visual impairments; low vision and blindness: human computer interaction; future perspectives for ageing well: AAL tools, products, services; mobile healthcare and m-health apps for people with disabilities; and service and information provision.

A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

Social and behavioral science has for decades studied and recognized leadership as a social exchange between leaders and followers. But leadership is rather complex, and as such, it tends to lead to an increased interest within and across different disciplines. This book is an attempt to provide theoretical and empirical framework to better understand leadership challenges in various contexts. The authors cover an array of themes that span from an individual level to an organizational and societal level. In this volume, two sections are presented. The first section based on individual level focuses on different leadership styles and abilities, and the other section provides theories to understand leadership in public administration, in industrial settings and in nonprofit organizations.

M-health can be defined as the ‘emerging mobile communications and network technologies for healthcare systems.' This book paves the path toward understanding the future of m-health technologies and services and also introducing the impact of mobility on existing e-health and commercial telemedical systems. M-Health: Emerging Mobile Health Systems presents a new and forward-looking source of information that explores the present and future trends in the applications of current and emerging wireless communication and network technologies for different healthcare scenaria. It also provides a discovery path on the synergies between the 2.5G and 3G systems and other relevant computing and information technologies and how they prescribe the way for the next generation of m-health services. The book contains 47 chapters, arranged in five thematic sections: Introduction to Mobile M-health Systems, Smart Mobile Applications for Health Professionals, Signal, Image, and Video Compression for M-health Applications, Emergency Health Care Systems and Services, Echography Systems and Services, and Remote and Home Monitoring. This book is intended for all those working in the field of information technologies in biomedicine, as well as for people working in future applications of wireless communications and wireless telemedical systems. It provides different levels of material to researchers, computing engineers, and medical practitioners interested in emerging e-health systems. This book will be a useful reference for all the readers in this important and growing field of research, and will contribute to the roadmap of future m-health systems and improve the development of effective healthcare delivery systems.

Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with "big data" are turning the medical sciences into a data-intensive science. To keep pace with the growing amounts of complex data, smart hospital approaches are a commandment of the future, necessitating context aware computing along with advanced interaction paradigms in new physical-digital ecosystems. The very successful synergistic combination of methodologies and approaches from Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions for the vision to support human intelligence with machine learning. The papers selected for this volume focus on hot topics in smart health; they discuss open problems and future challenges in order to provide a research agenda to stimulate further research and progress.

Smart Homes (SH) offer a promising approach to assisted living for the ageing population. Yet the main obstacle to the rapid development and deployment of Smart Home (SH) solutions essentially arises from the nature of the SH field, which is multidisciplinary and involves diverse applications and various stakeholders. Accordingly, an alternative to a one-size-fits-all approach is needed in order to advance the state of the art towards an open SH infrastructure. This book makes a valuable and critical contribution to smart assisted living research through the development of new effective, integrated, and interoperable SH solutions. It focuses on four underlying aspects: (1) Sensing and Monitoring Technologies; (2) Context Interference and Behaviour Analysis; (3) Personalisation and Adaptive Interaction, and (4) Open Smart Home and Service Infrastructures, demonstrating how fundamental theories, models and algorithms can be exploited to solve real-world problems. This comprehensive and timely book offers a unique and essential reference guide for policymakers, funding bodies, researchers, technology developers and managers, end users, carers, clinicians, healthcare service providers, educators and students, helping them adopt and implement smart assisted living systems.

Health Care Paradigms in the Internet of Things Ecosystem brings all IoT-enabled health care related technologies into a single platform so that undergraduate and postgraduate students, researchers, academicians and industry leaders can easily understand IoT-based healthcare systems. The book uses data and network engineering and intelligent decision support system-by-design principles to design a reliable IoT-enabled health care ecosystem and to implement cyber-physical pervasive infrastructure solutions. It takes the reader on a journey that begins with understanding the healthcare monitoring paradigm in IoT-enabled technologies and how it can be applied in various aspects. In addition, the book walks readers through real-time challenges and presents a guide on how to build a safe infrastructure for IoT-based health care. It also helps researchers and practitioners understand the e-health care architecture through IoT and the state-of-the-art in IoT countermeasures. Readers will find this to be a comprehensive discussion on functional frameworks for IoT-based healthcare systems, intelligent medicine, RFID technology, HMI, Cognitive Interpretation, Brain-Computer Interface, Remote Health Monitoring systems, wearable sensors, WBAN, and security and privacy issues in IoT-based health care monitoring systems. Presents the complete functional framework workflow in IoT-enabled healthcare technologies Explains concepts of location-aware protocols and decisive mobility in IoT healthcare Provides complete coverage of intelligent data processing and wearable sensor technologies in IoT-enabled healthcare Explores the Human Machine Interface and its implications in patient-care systems in IoT healthcare Explores security and privacy issues and challenges related to data-intensive technologies in healthcare-based Internet of Things

In the United States, some populations suffer from far greater disparities in health than others. Those disparities are caused not only by fundamental differences in health status across segments of the population, but also because of inequities in factors that impact health status, so-called determinants of health. Only part of an individual's health status depends on his or her behavior and choice; community-wide problems like poverty, unemployment, poor education, inadequate housing, poor public transportation, interpersonal violence, and decaying neighborhoods also contribute to health inequities, as well as the historic and ongoing interplay of structures, policies, and norms that shape lives. When these factors are not optimal in a community, it does not mean they are intractable: such inequities can be mitigated by social policies that can shape health in powerful ways. Communities in Action: Pathways to Health Equity seeks to delineate the causes of and the solutions to health inequities in the United States. This report focuses on what communities can do to promote health equity, what actions are needed by the many and varied stakeholders that are part of communities or support them, as well as the root causes and structural barriers that need to be overcome.

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges

The anthrax incidents following the 9/11 terrorist attacks put the spotlight on the nation’s public health agencies, placing it under an unprecedented scrutiny that added new dimensions to the complex issues considered in this report. The Future of the Public’s Health in the 21st Century reaffirms the vision of Healthy People 2010, and outlines a systems approach to assuring the nation’s health in practice, research, and policy. This approach focuses on joining the unique resources and perspectives of diverse sectors and entities and challenges these groups to work in a concerted, strategic way to promote and protect the public’s health. Focusing on diverse partnerships as the framework for public health, the book discusses: The need for a shift from an individual to a population-based approach in practice, research, policy, and community engagement. The status of the governmental public health infrastructure and what needs to be improved, including its interface with the health care delivery system. The roles nongovernment actors, such as academia, business, local communities and the media can play in creating a healthy nation. Providing an accessible analysis, this book will be important to public health policy-makers and practitioners, business and community leaders, health advocates, educators and journalists.

Clinical Application of Neuromuscular Techniques, Volume 2 - The Lower Body discusses the theory and practice of the manual treatment of chronic pain, especially with regards to the soft tissues of the lower body. Authored by experts of international renown, this highly successful book provides a structural review of each region, including ligaments and functional anatomy, and includes step-by-step protocols that address each muscle of a region. The volume now comes with an EVOLVE site for instructors who can download the full text and images for teaching purposes. Provides a comprehensive ‘one-stop’ volume on the treatment of somatic pain and dysfunction Designed and written to meet the needs of those working with neuromuscular dysfunction in a variety of professions All muscles covered from the perspective of assessment and treatment of myofascial pain Describes normal anatomy and physiology as well as the associated dysfunction Gives indications for treatments and guidance on making the appropriate treatment choice for each patient Combines NMT, MET, PR and much more to give a variety of treatment options for each case Describes the different NMT techniques in relation to the joint anatomy involved Practical step-by-step descriptions provided to make usage easy Includes acupuncture, hydrotherapies and nutritional support as well as guidance for the patient in the use of self-help approaches Contains up-to-date evidence based content Presents the latest research findings underpinning the practice of NMT methodology from differing areas of practice Presents the increasingly refined ways of using the variety of MET methods to allow the reader to safely apply them in a variety of settings

Infectious disease surveillance has evolved at an extraordinarypace during the past several decades, and continues to do so. It isincreasingly used to inform public health practice in addition toits use as a tool for early detection of epidemics. It is thereforecrucial that students of public health and epidemiology have asound understanding of the concepts and principles that underpinmodern surveillance of infectious disease. Written by leaders in the field, who have vast hands-onexperience in conducting surveillance and teaching applied publichealth, Concepts and Methods in Infectious DiseaseSurveillance is comprised of four sections. The first sectionprovides an overview, a description of systems used by publichealth jurisdictions in the United States and legal considerationsfor surveillance. The second section presents chapters on majorprogram-area or disease-specific surveillance systems, includingthose that monitor bacterial infections, foodborne diseases,healthcare-associated infections, and HIV/AIDS. The followingsection is devoted to methods for conducting surveillance and alsoapproaches for data analysis. A concluding section summarizescommunication of surveillance findings, including the use oftraditional and social media, in addition to showcasing lessonslearned from the New York City Department of Health’sexperience in surveillance and epidemiology training. This comprehensive new book covers major topics at an introductoryto intermediate level, and will be an excellent resource forinstructors. Suitable for use in graduate level courses in publichealth, human and veterinary medicine, and in undergraduateprograms in public-health-oriented disciplines, Concepts andMethods in Infectious Disease Surveillance is also a usefulprimer for frontline public health practitioners, hospitalepidemiologists, infection control practitioners, laboratorians inpublic health settings, infectious disease researchers, and medicaland public health informaticians interested in a concise overviewof infectious disease surveillance.

Smart Healthcare for Disease Diagnosis and Prevention focuses on the advancement in healthcare technology to improve human health at all levels using smart technologies. It covers all necessary topics from basic concepts (such as signal and image processing) to advanced knowledge on topics such as tissue engineering, virtual and intelligent instrumentation (or VLSI) and Embedded Systems. This book can be used to guide students and young researchers, providing basic knowledge on signal/image processing and smart technologies. Users will find a perfect blend of the interdisciplinary approach to biomedical engineering. The book considers many technical concepts, emerging technologies, real-world healthcare applications, and many other technical, multidisciplinary notions in the same content. Finally, it systemically introduces the technologies and devices for healthcare objects and targets disease diagnosis and prevention in different views. Discusses how new advanced technologies are used in real healthcare applications to improve patient safety Explores how medical data such as signals and images can be used in diagnosis Covers how wireless communications devices, such as sensor networks, RFID, wireless body area network, and wearable sensors are used in the medical environment

This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.