Mobile Computing Solutions For Healthcare Systems

This book focuses on recent developments in integrating AI, machine learning methods, medical image processing, advanced network security, and advanced antenna design techniques to implement practical Mobile Health (M-Health) systems. The editors bring together researchers and practitioners who address several developments in the field of M-Health. Chapters highlight intelligent healthcare IoT and Machine Learning based systems for personalized healthcare delivery and remote monitoring applications. The contents also explain medical applications of computing technologies such as Wireless Body Area Networks (WBANs), wearable sensors, multi-factor authentication, and cloud computing. The book is intended as a handy resource for undergraduate and graduate biomedical engineering students and mobile technology researchers who want to know about the recent trends in mobile health technology.

CLOUD COMPUTING SOLUTIONS The main purpose of this book is to include all the cloud-related technologies in a single platform, so that researchers, academicians, postgraduate students, and those in the industry can easily understand the cloud-based ecosystems. This book discusses the evolution of cloud computing through grid computing and cluster computing. It will help researchers and practitioners to understand grid and distributed computing cloud infrastructure, virtual machines, virtualization, live migration, scheduling techniques, auditing concept, security and privacy, business models, and case studies through the state-of-the-art cloud computing countermeasures. This book covers the spectrum of cloud computing-related technologies and the wide-ranging contents will differentiate this book from others. The topics treated in the book include: The evolution of cloud computing from grid computing, cluster computing, and distributed systems; Covers cloud computing and virtualization environments; Discusses live migration, database, auditing, and applications as part of the materials related to cloud computing; Provides concepts of cloud storage, cloud strategy planning, and management, cloud security, and privacy issues; Explains complex concepts clearly and covers information for advanced users and beginners. Audience The primary audience for the book includes IT, computer science specialists, researchers, graduate students, designers, experts, and engineers who are occupied with research.

The use of mobile devices in medical care settings and by wellness professionals has influenced and changed many aspects of clinical practice. Mobile devices have become ubiquitous in these settings, leading to rapid growth in the development of medical apps. Contemporary Applications of Mobile Computing in Healthcare Settings is a critical scholarly resource that explores the benefits of using mobile devices and apps in the medical field and examines the shortcomings in the validation practices regarding these technologies. Featuring coverage on a wide range of topics such as smart healthcare, patient surveillance, and body fitness monitoring, this book is geared toward academicians, nurses, medical professionals, practitioners, and students seeking current research on the quality and safety of the apps currently available for use by medical care professionals.

The implementation of cloud technologies in healthcare is paving the way to more effective patient care and management for medical professionals around the world. As more facilities start to integrate cloud computing into their healthcare systems, it is imperative to examine the emergent trends and innovations in the field. Cloud Computing Systems and Applications in Healthcare features innovative research on the impact that cloud technology has on patient care, disease management, and the efficiency of various medical systems. Highlighting the challenges and difficulties in implementing cloud technology into the healthcare field, this publication is a critical reference source for academicians, technology designers, engineers, professionals, analysts, and graduate students.

The pervasive healthcare system focus towards achieving two specific goals: the availability of eHealth applications and medical information anywhere and anytime and the invisibility of computing. Furthermore, pervasive health system encompasses new types of sensing and communication of health information as well as new type of interactions among health providers and people, among patients, among patients and researchers and patients and corporations. This book aims at promoting the discussion on current trends in technologies and concepts that help integrate health monitoring and healthcare more seamlessly to our everyday lives, regardless of space and time, but also present cutting edge perspectives and visions to highlight future development. The book presents not only the state of the art technologies and solutions to tackle the critical challenges faced by the building and development of the pervasive health system but also potential impact on society at social, medical and technological level.

mHealth: From Smartphone to Smart Systems provides a high level and comprehensive survey of the emergence of mobile technology healthcare. This book looks beyond the already-popular devices and apps associated with mHealth, exploring the major role this technology could play as healthcare steers inexorably toward an architecture

This book provides a framework for evaluating big data and cloud computing based on how they evolve to fit users’ needs in developing countries in key areas, such as agriculture and education. The authors discuss how this framework can be utilized by businesses, governments, and consumers to accelerate economic growth and overcome information and communication barriers. By examining the ways in which cloud computing can drive social, economic, and environmental transformation, readers gain a nuanced understanding of the opportunities and challenges these technologies offer. The authors also provide an authoritative and up-to-date account of big data’s diffusion into a wide range of developing economies, such as Brazil and China, illustrating key concepts through in-depth case studies. Special attention is paid to economic development in the context of the new Sustainable Development Goals formulated by the United Nations, introducing readers to the most modern standard of economic evaluation. Students of information management, entrepreneurship, and development, as well as policy makers, researchers, and practitioners, will find Big Data and Cloud Computing for Development an interesting read and a useful reference source.

This book is a detailed exploration of mobile technologies in the healthcare sector. It begins with an overview of WiFi-based systems for activity recognition, utilizing existing infrastructure for health monitoring, and then examines mmWave technology for its precision in health systems and the design of a sophisticated fitness assistant system. The narrative progresses to wearable technologies, emphasizing their role in personal fitness and injury prevention. A significant focus is on eating habit monitoring for comprehensive dietary analysis. The book concludes with an innovative use of PPG sensors in wearables for intricate applications, suck as gesture recognition and user authentication. Looking ahead, this book outlines future research directions, emphasizing the importance of securing deep learning techniques in mobile health technologies, developing adaptive systems for dynamic environments, and creating integrated systems for personalized medicine and comprehensive health monitoring. This forward-looking perspective highlights the need for proactive, preventive and tailored healthcare solutions. This book also discusses various challenges in designing effective and robust mobile healthcare systems. One of the major challenges is collecting accurate and reliable sensor data, given the complexity and variability of human activities. It tackles this challenge through innovative sensing modalities like WiFi, millimeter wave signals, and photoplethysmography that can capture fine-grained details regarding human activities and physiology. Robust algorithms are designed to extract meaningful features from the sensor data to interpret activities, gestures, and biometrics. System robustness across diverse environments is another big challenge in mobile healthcare. The solutions presented by this book could adapt to different settings using advanced learning techniques such as environment-invariant analysis and domain adaptation training. The book also deals with practical issues like reducing training efforts, handling motion artifacts and implementing systems using commercially available devices. Overall, this book provides comprehensive methodologies leveraging cutting-edge mobile technologies to address key challenges in developing real-world healthcare applications for continuous monitoring, personalized assistance, dietary tracking, gesture recognition and user authentication. The systems are designed to work reliably despite environmental variations, individual differences, and device constraints. The primary audience for this book targets researchers working in mobile computing, smart healthcare, human-computer interaction, cyber-physical systems, AI/ML and cybersecurity. Specifically, it targets advanced-level students majoring in electronic engineering, computer engineering, computer science, biomedical engineering, data science, biobehavioral health and information science. Professional and consultants focusing on advancing mobile computing, smart healthcare, human-computer interaction, Internet-of-Things, and cybersecurity through the application of sensing modalities, signal processing and AI/ML will also find this book highly valuable.