This book covers the results of a study concerning systems for healthcare-oriented monitoring of elderly persons. It is focused on the methods for processing data from impulse-radar sensors and depth sensors, aimed at localisation of monitored persons and estimation of selected quantities informative from the healthcare point of view. It includes mathematical descriptions of the considered methods, as well as the corresponding algorithms and the results of their testing in a real-world context. Moreover, it explains the motivations for developing healthcare-oriented monitoring systems and specifies the real-world needs which may be addressed by such systems. The healthcare systems, all over the world, are confronted with challenges implied by the ageing of population and the lack of adequate recruitment of healthcare professionals. Those challenges can be met by developing new technologies aimed at improving the quality of life of elderly people and at increasing the efficiency of public health management. Monitoring systems may contribute to this strategy by providing information on the evolving health status of independently-living elderly persons, enabling healthcare personnel to quickly react to dangerous events. Although these facts are generally acknowledged, such systems are not yet being commonly used in healthcare facilities and households. This may be explained by the difficulties related to the development of technological solutions which can be both acceptable for monitored persons and capable of providing healthcare personnel with useful information. The impulse-radar sensors and depth sensors, considered in this book, have a potential for overcoming those difficulties since they are not cumbersome for the monitored persons - if compared to wearable sensors - and do not violate the monitored person's privacy - if compared to video cameras. Since for safety reasons the level of power, emitted by the radar sensors, must be ultra-low, the task of detection and processing of signals is a research challenge which requires more sophisticated methods than those developed for other radar applications. This book contains descriptions of new Bayesian methods, applicable for the localisation of persons by means of impulse-radar sensors, and an exhaustive review of previously published ones. Furthermore, the methods for denoising, regularised numerical differentiation and fusion of data from impulse-radar sensors and depth sensors are systematically reviewed in this book. On top of that, the results of experiments aimed at comparing the performance of various data-processing methods, which may serve as guidelines for related future projects, are presented.

This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners.

This book presents state-of-the-art research methods, results, and applications in social media and health research. It aims to help readers better understand the different aspects of using social web platforms in health research. Throughout the chapters, the benefits, limitations, and best practices of using a variety of social web platforms in health research are discussed with concrete use cases. This is an ideal book for biomedical researchers, clinicians, and health consumers (including patients) who are interested in learning how social web platforms impact health and healthcare research.

This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical, methodological, well-established, and validated empirical work in these fields. Artificial intelligence and IoT are set to revolutionize all industries, but perhaps none so much as health care. Both biomedicine and machine learning applications are capable of analyzing data stored in national health databases in order to identify potential health problems, complications and effective protocols, and a range of wearable devices for biomedical and healthcare applications far beyond tracking individuals' steps each day has emerged. These prosthetic technologies have made significant strides in recent decades with the advances in materials and development. As a result, more flexible, more mobile chip-enabled prosthetics or other robotic devices are on the horizon. For example, IoT-enabled wireless ECG sensors that reduce healthcare cost, and lead to better quality of life for cardiac patients. This book focuses on three current trends that are likely to have a significant impact on future healthcare: Advanced Medical Imaging and Signal Processing; Biomedical Sensors; and Biotechnological and Healthcare Advances. It also presents new methods of evaluating medical data, and diagnosing diseases in order to improve general quality of life.

This book highlights progress in terms of Virus Biology and Infection Detection, Prevention, and Control, along with Screening, Testing, and Detection Techniques, that will provide learners and researchers (from basic to advanced) with the most innovative computer-driven methodologies for the fight against COVID-19. In addition, this book also covers the Pre- and Post-Impact of the COVID-19 Pandemic Crisis that will definitely provide useful content for researchers to think broadly about the analytical areas affected by COVID-19. This ultimately shows different paths to the same destination to help understand the nature of the COVID-19 pandemic and how to avoid it in the future.

This book provides a comprehensive introduction to computational epidemiology, highlighting its major methodological paradigms throughout the development of the field while emphasizing the needs for a new paradigm shift in order to most effectively address the increasingly complex real-world challenges in disease control and prevention. Specifically, the book presents the basic concepts, related computational models, and tools that are useful for characterizing disease transmission dynamics with respect to a heterogeneous host population. In addition, it shows how to develop and apply computational methods to tackle the challenges involved in population-level intervention, such as prioritized vaccine allocation. A unique feature of this book is that its examination on the issues of vaccination decision-making is not confined only to the question of how to develop strategic policies on prioritized interventions, as it further approaches the issues from the perspective of individuals, offering a well integrated cost-benefit and social-influence account for voluntary vaccination decisions. One of the most important contributions of this book lies in it offers a blueprint on a novel methodological paradigm in epidemiology, namely, systems epidemiology, with detailed systems modeling principles, as well as practical steps and real-world examples, which can readily be applied in addressing future systems epidemiological challenges. The book is intended to serve as a reference book for researchers and practitioners in the fields of computer science and epidemiology. Together with the provided references on the key concepts, methods, and examples being introduced, the book can also readily be adopted as an introductory text for undergraduate and graduate courses in computational epidemiology as well as systems epidemiology, and as training materials for practitioners and field workers.

Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem. Key Features: Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codes Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers Presents descriptive data driven methods for the high utilizer population Identifies a best-fitting linear and tree-based regression model to account for patients' acute and chronic condition loads and demographic characteristics

This edited book helps researchers and practitioners to understand e-health, m-healthcare architecture through IoT and the state of the art in IoT counter measures. This book provides a comprehensive discussion on a functional framework for IoT-based healthcare systems, intelligent medicine box, RFID technology, HMI, cognitive interpretation, BCI, remote health monitoring systems, wearable sensors, WBAN, healthcare analytics, machine learning (ML) techniques for IoT-enabled healthcare services, security and privacy issues in IoT-based healthcare monitoring systems. The book discusses integration of IoT with big data and cloud computing for solving several real-time problems by the use of smart healthcare applications. In these applications, the cloud computing provides a common workplace for IoT and big data, big data provides data analytics technology and IoT provides the source of data. It serves as a reference resource for researchers and practitioners in academia and industry.

The exponential growth of the Internet in recent years has given individuals immediate and virtually anonymous access to all types of information, including explicit sexual content. While many celebrate the personal freedoms made possible by the Internet, others consider unfettered access to online sexual material to be an unhealthy, if not dangerous phenomenon. Expanding this debate, Cybersex: The Dark Side of the Force presents for the first time an empirical foundation for the discussion of cybersex compulsivity and its effect on the mental health of individuals, couples, teens, and young children.
While pornographic material has long been available to the consumer in print and video form, these purchases are inherently limited by the individual's degree of comfort with the public exposure (however minimal) that they they require. In contrast, the Internet provides a forum where children can access unsuitable material without parental supervision, and where individuals with existing sexual compulsions can acces material that can exacerbate their struggle to maintain control over their desire. Even among individuals who are not as susceptible to such material, cybersex can create distorted associations or compound negative or unrealistic expectations about sexuality.
This groundbreaking examination of cybersex was originally published as a special issue of the journal Sexual Addiction and Compulsivity. It is a crucial resource for sex therapists, who until now had no rigorous study of the effect of online pornography on the patients they treat. It will also be of great interest to general marriage and family therapists who find themselves dealing with this issue with their clients, as well as others who are interested in the Internet as a social phenomenon.

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This is a practical book for health and IT professionals who need to ensure that patient safety is prioritized in the design and implementation of clinical information technology. Healthcare professionals are increasingly reliant on information technology to deliver care and inform their clinical decision making. Health IT provides enormous benefits in efficiency, communication and decision making. However a number of high-profile UK and US studies have concluded that when Health IT is poorly designed or sub-optimally implemented then patient safety can be compromised. Manufacturers and healthcare organizations are increasingly required to demonstrate that their Health IT solutions are proactively assured. Surprisingly the majority of systems are not subject to regulation so there is little in the way of practical guidance as to how risk management can be achieved. The book fills that gap. The author, a doctor and IT professional, harnesses his two decades of experience to characterize the hazards that health technology can introduce. Risk can never be eliminated but by drawing on lessons from other safety-critical industries the book systematically sets out how clinical risk can be strategically controlled. The book proposes the employment of a Safety Case to articulate and justify residual risk so that not only is risk proactively managed but it is seen to be managed. These simple techniques drive product quality and allow a technology's benefits to be realized without compromising patient safety.

Embedded systems have long become essential in application areas in which human control is impossible or infeasible. The development of modern embedded systems is becoming increasingly difficult and challenging because of their overall system complexity, their tighter and cross-functional integration, the increasing requirements concerning safety and real-time behavior, and the need to reduce development and operation costs. This book provides a comprehensive overview of the Software Platform Embedded Systems (SPES) modeling framework and demonstrates its applicability in embedded system development in various industry domains such as automation, automotive, avionics, energy, and healthcare. In SPES 2020, twenty-one partners from academia and industry have joined forces in order to develop and evaluate in different industrial domains a modeling framework that reflects the current state of the art in embedded systems engineering. The content of this book is structured in four parts. Part I "Starting Point" discusses the status quo of embedded systems development and model-based engineering, and summarizes the key requirements faced when developing embedded systems in different application domains. Part II "The SPES Modeling Framework" describes the SPES modeling framework. Part III "Application and Evaluation of the SPES Modeling Framework" reports on the validation steps taken to ensure that the framework met the requirements discussed in Part I. Finally, Part IV "Impact of the SPES Modeling Framework" summarizes the results achieved and provides an outlook on future work. The book is mainly aimed at professionals and practitioners who deal with the development of embedded systems on a daily basis. Researchers in academia and industry may use it as a compendium for the requirements and state-of-the-art solution concepts for embedded systems development.

This book provides a comprehensive overview of various aspects of the development of smart cities from a secure, trusted, and reliable data transmission perspective. It presents theoretical concepts and empirical studies, as well as examples of smart city programs and their capacity to create value for citizens. The contributions offer a panorama of the most important aspects of smart city evolution and implementation within various frameworks, such as healthcare, education, and transportation. Comparing current advanced applications and best practices, the book subsequently explores how smart environments and programs could help improve the quality of life in urban spaces and promote cultural and economic development.

This book emphasizes the latest developments and achievements in artificial intelligence and related technologies, focusing on the applications of artificial intelligence and medical diagnosis. The book describes the theory, applications, concept visualization, and critical surveys covering most aspects of AI for medical informatics.

This book offers a comprehensive yet concise overview of the challenges and opportunities presented by the use of artificial intelligence in healthcare. It does so by approaching the topic from multiple perspectives, e.g. the nursing, consumer, medical practitioner, healthcare manager, and data analyst perspective. It covers human factors research, discusses patient safety issues, and addresses ethical challenges, as well as important policy issues. By reporting on cutting-edge research and hands-on experience, the book offers an insightful reference guide for health information technology professionals, healthcare managers, healthcare practitioners, and patients alike, aiding them in their decision-making processes. It will also benefit students and researchers whose work involves artificial intelligence-related research issues in healthcare.

This second edition of Human Factors Methods: A Practical Guide for Engineering and Design now presents 107 design and evaluation methods as well as numerous refinements to those that featured in the original. The book has been carefully designed to act as an ergonomics methods manual, aiding both students and practitioners. The eleven sections represent the different categories of ergonomics methods and techniques that can be used in the evaluation and design process. Offering a 'how-to' text on a substantial range of ergonomics methods that can be used in the design and evaluation of products and systems, it is a comprehensive point of reference for all these methods. An overview of the methods is presented in chapter one, with a methods matrix showing which can be used in conjunction. The following chapters detail the methods showing how to apply them in practice. Flowcharts, procedures and examples cover the requirements of a diverse audience and varied applications of the methods. The final chapter, a new addition, illustrates the EAST method, which integrates several well-known methods into a teamwork analysis approach.

This book examines the concept of dignity from a variety of global perspectives. It scrutinizes how dignity informs policy and practice, and is influenced by international and domestic law, human rights values, and domestic politics. An exciting collection of essays, this edited volume provides an analysis of human rights as they are experienced by real people who have in many cases been forced to take action to further their own interests. Readers will discover an extensive range of issues discussed, from the internet, climate change and disabilities, to globalization, old-age, and migrants' rights. The last section deals with the impact of various issues on indigenous and migrant populations, specifically violence in Columbia, border issues in Tijuana, women's and children's rights violations, and the complex problems experienced by refugees, particularly in regards to citizenship. The interdisciplinary nature of this work makes it an invaluable read for scholars of Health Studies, Law, Human Rights, Sociology and Politics.

Founded in 2004, the Games for Health Project supports community, knowledge and business development efforts to use cutting-edge games and game technologies to improve health and health care. The Games for Health Conference brings together researchers, medical professionals and game developers to share information about the impact of games, playful interaction and game technologies on health, health care and policy. Over two days, more than 400 attendees participate in over 60 sessions provided by an international array of 80+ speakers, cutting across a wide range of activities in health and health care. Topics include exergaming, physical therapy, disease management, health behavior change, biofeedback, rehab, epidemiology, training, cognitive health, nutrition and health education.

This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.

This book provides a comprehensive explanation of precision (i.e., personalized) healthcare and explores how it can be advanced through artificial intelligence (AI) and other data-driven technologies. From improving the diagnosis, treatment, and monitoring of many medical conditions to the effective implementation of precise patient care, this book will help you understand datasets produced from digital health technologies and IoT and teach you how to employ analytical methods such as convolutional neural networks and deep learning to analyze that data. You'll also see how this data-driven approach can enhance and democratize value-based healthcare delivery. Additionally, you'll learn how the convergence of AI and precision health is revolutionizing healthcare, including some of the most difficult challenges facing precision medicine, such as ethics, bias, privacy, and health equity. Precision Health and Artificial Intelligence provides the groundwork for clinicians, engineers, bioinformaticians, and healthcare enthusiasts to apply AI to healthcare. What You Will Learn Understand the components required to facilitate precision health and personalized care Apply and implement precision health systems Overcome the challenges of delivering precision healthcare at scale Reconcile ethical and moral implications of delivering precision healthcare Gain insight into the hurdles providers face while implementing precision healthcare Who This Book Is For Healthcare professionals, clinicians, engineers, bioinformaticians, chief information officers (CIOs), and students

This book defines the phenomenon of mHealth and its evolution, explaining why an understanding of mHealth is critical for decision makers, entrepreneurs and policy analysts who are pivotal to developing products that meet the collaborative health information needs of consumers and providers in a competitive and rapidly-changing environment. The book examines trends in mHealth and discusses how mHealth technologies offer opportunities for innovators and entrepreneurs, those who often are industry first-movers with regard to technology advancement. It also explores the changing dynamics and relationships among physicians, patients, insurers, regulators, managers, administrators, caregivers and others involved in the delivery of health services. The primary focus is on the ways in which mHealth technologies are revising and reshaping healthcare delivery systems in the United States and globally and how those changes are expected to change the ways in which the business of healthcare is conducted. mHealth: Transforming Healthcare consists of nine chapters that addresses key content areas, including history (to the extent that dynamic technologies have a history), projection of immediate evolution and consistent issues associated with health technology, such as security and information privacy and government and industry regulation. A major point of discussion addressed is whether mHealth is a transient group of products and a passing patient encounter approach, or if it is the way much of our health care will be delivered in future years with incremental evolution to achieve sustainable innovation of health technologies.

This book analyses the role of technology in the realm of health. Health apps can promote medicalization and the idea that health is an individual matter, rather than a political and social one. The authors base their arguments around three theoretical frameworks. Quantification: the growing importance in our society of markers, rankings, and scores, which thanks to digital devices is fueled by the ease with which it is now possible to collect data. Gamification: a powerful trend in digital society, using playful features to transform what are seen as dull tasks into competitive and appealing ones. Gamified self-tracking seemingly increases our productivity without oppressing us with apparent self-governance. Finally, Medicalization: a growing social phenomenon of the transformation of a 'normal' condition into something pathological. Several health apps presuppose a conception of the user as an individualized subject divorced from any social determinants of health. The authors investigate the possibility of people sharing their most private states leading to new forms of algorithmic surveillance. Alongside this negative vision of medicalization the authors recover the now-rare concept of positive medicalization, looking at how apps can work as positive self-help devices though promoting a medical framework. A selection of digital programs related to fitness in the workplace are also presented and discussed.

Digital Playgrounds explores the key developments, trends, debates, and controversies that have shaped children's commercial digital play spaces over the past two decades. It argues that children's online playgrounds, virtual worlds, and connected games are much more than mere sources of fun and diversion - they serve as the sites of complex negotiations of power between children, parents, developers, politicians, and other actors with a stake in determining what, how, and where children's play unfolds. Through an innovative, transdisciplinary framework combining science and technology studies, critical communication studies, and children's cultural studies, Digital Playgrounds focuses on the contents and contexts of actual technological artefacts as a necessary entry point for understanding the meanings and politics of children's digital play. The discussion draws on several research studies on a wide range of digital playgrounds designed and marketed to children aged six to twelve years, revealing how various problematic tendencies prevent most digital play spaces from effectively supporting children's culture, rights, and - ironically - play. Digital Playgrounds lays the groundwork for a critical reconsideration of how existing approaches might be used in the development of new regulation, as well as best practices for the industries involved in making children's digital play spaces. In so doing, it argues that children's online play spaces be reimagined as a crucial new form of public sphere in which children's rights and digital citizenship must be prioritized.

This book explores a number of important issues in the area of occupational safety and hygiene. Presenting both research and best practices for the evaluation of occupational risk, safety and health in various types of industry, it particularly focuses on occupational safety in automated environments, innovative management systems and occupational safety in a global context. The different chapters examine the perspectives of all those involved, such as managers, workers and OSH professionals. Based on selected contributions presented at the 15th International Symposium on Occupational Safety and Hygiene (SHO 2019), held on 15-16 April, 2019, in Guimaraes, Portugal, the book serves as a timely reference guide and source of inspiration to OSH researchers, practitioners and organizations operating in a global context.

This book deals with two important technologies in human-computer interaction: computer generation of synthetic speech and computer recognition of human speech. It addresses the problems in generating speech with varying precision of articulation and how to convey moods and attitudes.

This book analyses the role of technology in the realm of health. Health apps can promote medicalization and the idea that health is an individual matter, rather than a political and social one. The authors base their arguments around three theoretical frameworks. Quantification: the growing importance in our society of markers, rankings, and scores, which thanks to digital devices is fueled by the ease with which it is now possible to collect data. Gamification: a powerful trend in digital society, using playful features to transform what are seen as dull tasks into competitive and appealing ones. Gamified self-tracking seemingly increases our productivity without oppressing us with apparent self-governance. Finally, Medicalization: a growing social phenomenon of the transformation of a 'normal' condition into something pathological. Several health apps presuppose a conception of the user as an individualized subject divorced from any social determinants of health. The authors investigate the possibility of people sharing their most private states leading to new forms of algorithmic surveillance. Alongside this negative vision of medicalization the authors recover the now-rare concept of positive medicalization, looking at how apps can work as positive self-help devices though promoting a medical framework. A selection of digital programs related to fitness in the workplace are also presented and discussed.