Mobile Health

This book offers a comprehensive report on the technological aspects of Mobile Health (mHealth) and discusses the main challenges and future directions in the field. It is divided into eight parts: (1) preventive and curative medicine; (2) remote health monitoring; (3) interoperability; (4) framework, architecture, and software/hardware systems; (5) cloud applications; (6) radio technologies and applications; (7) communication networks and systems; and (8) security and privacy mechanisms. The first two parts cover sensor-based and bedside systems for remotely monitoring patients’ health condition, which aim at preventing the development of health problems and managing the prognosis of acute and chronic diseases. The related chapters discuss how new sensing and wireless technologies can offer accurate and cost-effective means for monitoring and evaluating behavior of individuals with dementia and psychiatric disorders, such as wandering behavior and sleep impairments. The following two parts focus on architectures and higher level systems, and on the challenges associated with their interoperability and scalability, two important aspects that stand in the way of the widespread deployment of mHealth systems. The remaining parts focus on telecommunication support systems for mHealth, including radio technologies, communication and cloud networks, and secure health-related applications and systems. All in all, the book offers a snapshot of the state-of-art in mHealth systems, and addresses the needs of a multidisciplinary audience, including engineers, computer scientists, healthcare providers, and medical professionals, working in both academia and the industry, as well as stakeholders at government agencies and non-profit 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.

This volume provides a comprehensive introduction to mHealth technology and is accessible to technology-oriented researchers and practitioners with backgrounds in computer science, engineering, statistics, and applied mathematics. The contributing authors include leading researchers and practitioners in the mHealth field. The book offers an in-depth exploration of the three key elements of mHealth technology: the development of on-body sensors that can identify key health-related behaviors (sensors to markers), the use of analytic methods to predict current and future states of health and disease (markers to predictors), and the development of mobile interventions which can improve health outcomes (predictors to interventions). Chapters are organized into sections, with the first section devoted to mHealth applications, followed by three sections devoted to the above three key technology areas. Each chapter can be read independently, but the organization of the entire book provides a logical flow from the design of on-body sensing technology, through the analysis of time-varying sensor data, to interactions with a user which create opportunities to improve health outcomes. This volume is a valuable resource to spur the development of this growing field, and ideally suited for use as a textbook in an mHealth course.

This book examines the current status of mHealth development, regulations and the social background in Japan, South Korea and China, comparing it to the situation in the United States and the European Union and consider solutions to issues surrounding mHealth. The recent progress in mobile technology, represented by smartphones and smart watches, has been remarkable. A service called mobile health (mHealth), which uses such mobile technology to manage health, is also becoming a reality. Although the accuracy of medical devices is not as accurate as those used in medicine, the biometric information such as heart rate and SpO2 can already be monitored over a long period of time. Although the technology is maturing to the point where it can be implemented in society, it remains an unapproved service of medical care in most countries. The development and social implementation of mHealth is most active in the US, but social implementation is gradually progressing in other countries as well. In this book, we will first discuss what kind of global and harmonized regulations are desirable by comparing the regulatory reforms necessary for social implementation of mHealth. In addition, mHealth raises privacy concerns in the US because the usual behavior and biometric information of subjects is utilized by private companies. In addition, it is important to note that the behavior and biometric information of subjects collected by smart devices is automatically analyzed by AI technology, mainly machine learning, which makes the analysis a black box.

"This book gives detailed analysis of the technology, applications and uses of mobile technologies in the healthcare sector by using case studies to highlight the successes and concerns of mobile health projects"--Provided by publisher.

One of the central engines of the current shift towards decentralization and reorientation of healthcare services is mobile healthcare (mHealth). mHealth offers unique opportunities to reduce cost, increase efficiencies, and improve quality and access to healthcare. However, the full impact of mHealth is just beginning to be felt by the medical community and requires further examination to understand the full range of benefits it contributes to medical staff and patients. Mobile Health Applications for Quality Healthcare Delivery explores the emergence of mHealth in the healthcare setting and examines its impact on patient-centered care, including how it has reshaped access, quality, and treatment. Highlighting topics such as patient management, emergency medicine, and health monitoring, this publication supports e-health systems designers in understanding how mobile technologies can best be used for the benefit of both doctors and their patients. It is designed for healthcare professionals, administrators, students, health services managers, and academicians.

The E-Medicine, E-Health, M-Health, Telemedicine, and Telehealth Handbook provides extensive coverage of modern telecommunication in the medical industry, from sensors on and within the body to electronic medical records and beyond. Telehealth and Mobile Health is the second volume of this handbook. Featuring chapters written by leading experts and researchers in their respective fields, this volume: Discusses telesurgery, medical robotics, and image guidance as well as telenursing and remote patient care Describes the implementation of networks, data management, record management, and effective personnel training Explains how the use of new technologies brings many business, management, and service opportunities Provides examples of scientific advancements such as brain-controlled bionic human arms and hands Incorporates clinical applications throughout for practical reference The E-Medicine, E-Health, M-Health, Telemedicine, and Telehealth Handbook bridges the gap between scientists, engineers, and medical professionals by creating synergy in the related fields of biomedical engineering, information and communication technology, business, and healthcare.

Smart health technologies continue to gain research interest across the globe in this digital era. Researchers are focusing on advancements in healthcare systems to make human life better. Also, such advancements help in early disease diagnosis and prevention of the worst diseases. Designing smart healthcare systems is possible only because of recent developments in artificial intelligence, machine learning and IoT technologies. Though mHealth refers to all mobile devices which can communicate data, mobile phones are presently the most popular platform for mHealth delivery. Ninety-four percent of the world population owns/uses a mobile phone, making mobile phones an optimal delivery platform for mHealth interventions. mHealth may catalyse the healthcare delivery model from a historical/episodic model into a tangible/patient-centric model. mHealth is being viewed progressively by many as an essential technology metaphor to achieve rich, vigorous patient engagement, ultimately achieving a patient-centric paradigm change.This book will discuss diverse topics to explain the rapidly emerging and evolving mobile health and artificial perspective, the emergence of integrated platforms and hosted third-party tools, and the development of decentralized applications for various research domains. It presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of as well as the hindrances to mHealth. The wide variety in topics it presents offers readers multiple perspectives on a variety of disciplines.The aim of this edited book is to publish the latest research advancements in the convergence of automation technology, artificial intelligence, biomedical engineering and health informatics. This will help readers to grasp the extensive point of view and the essence of recent advances in this field. This book solicits contributions which include theory, case studies and computing paradigms pertaining to healthcare applications. The prospective audience would be researchers, professionals, practitioners, and students from academia and industry who work in this field. We hope the chapters presented will inspire future research from both theoretical and practical viewpoints to spur further advances in the field. A brief introduction about each chapter follows. Chapter 1 focuses on the role of Internet of Things (IoT) technologies in healthcare which provides an overview of the various types of IoT devices and data generating equipment for medical information.In Chapter 2, the objective is to provide a brief discussion about the advantages and disadvantages of using IoT based technologies in healthcare such as wearable devices. Chapter 3 deals with important aspects of data science for healthcare systems, which includes various algorithms for decision support system algorithms. Chapter 4 discusses various innovative technologies like digital twins for healthcare and medical diagnosis.Chapter 5 discusses research investigating the long-term effects of pregnancy and lactation on the female body.Chapter 6 summarizes recent advances in machine and deep learning techniques for smart healthcare applications.Chapter 7 explores the research insights on using an artificial neural network with a wrapper-based feature selection to predict heart failure.Chapter 8 presents a review on context-aware mobile healthcare for smart health services in nursing homes.Chapter 9 focuses on certain machine learning methods that can help in early prediction of pandemics.Chapter 10 explores techniques and methods based on machine learning for malaria diagnosis.Chapter 11 is a complete discussion about mobile health technology to improve health-related quality of life of chronic disease patients in emerging economies.We are grateful to the authors and reviewers for their excellent contributions for making this book possible.