This book aims to provide a detailed understanding of IoMT-supported applications while engaging premium smart computing methods and improved algorithms in the field of computer science. It contains thirteen chapters discussing various applications under the umbrella of the Internet of Medical Things. These applications geared towards IoMT cloud analysis, machine learning, computer vision and deep learning have enabled the evaluation of the proposed solutions.
This book covers COVID-19 related research works and focuses on recent advances in the Internet of Things (IoT) in smart healthcare technologies. It includes reviews and original works on COVID-19 in terms of e-healthcare, medicine technology, life support systems, fast detection, diagnoses, developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, solutions for monitoring and control of the spread of COVID-19, among other topics. The book covers comprehensive studies from bioelectronics and biomedical engineering, artificial intelligence, and big data with a prime focus on COVID-19 pandemic.
Smart healthcare technology improves the diagnosis and treatment of patients, provides easy access to medical facilities and emergency care services, and minimizes the gaps between patients and healthcare providers. While clinical data protection remains a major challenge, innovations such as the internet of medical things and smart healthcare systems increase the efficiency and quality of patient care. Healthcare technology can only become faster, more profitable, and more flexible as additional research on its advancements is conducted and collected. Smart Medical Data Sensing and IoT Systems Design in Healthcare is an essential reference source that focuses on robust and easy solutions for the delivery of medical information from patients to doctors and explores low-cost, high-performance, highly efficient, deployable IoT system options in healthcare systems. Featuring research on topics such as hospital management systems, electronic health records, and bio-signals, this book is ideally designed for technologists, engineers, scientists, clinicians, biomedical engineers, hospital directors, doctors, nurses, healthcare practitioners, telemedical agents, students, and academicians seeking coverage on the latest technological developments in medical data analysis and connectivity.
This book looks at the growing segment of Internet of Things technology (IoT) known as Internet of Medical Things (IoMT), an automated system that aids in bridging the gap between isolated and rural communities and the critical healthcare services that are available in more populated and urban areas. Many technological aspects of IoMT are still being researched and developed, with the objective of minimizing the cost and improving the performance of the overall healthcare system. This book focuses on innovative IoMT methods and solutions being developed for use in the application of healthcare services, including post-surgery care, virtual home assistance, smart real-time patient monitoring, implantable sensors and cameras, and diagnosis and treatment planning. It also examines critical issues around the technology, such as security vulnerabilities, IoMT machine learning approaches, and medical data compression for lossless data transmission and archiving. Internet of Medical Things is a valuable reference for researchers, students, and postgraduates working in biomedical, electronics, and communications engineering, as well as practicing healthcare professionals.
Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. - Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning - Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics - Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies
INTERNET OF MEDICAL THINGS (IOMT) Providing an essential addition to the reference material available in the field of IoMT, this timely publication covers a range of applied research on healthcare, biomedical data mining, and the security and privacy of health records. With their ability to collect, analyze and transmit health data, IoMT tools are rapidly changing healthcare delivery. For patients and clinicians, these applications are playing a central part in tracking and preventing chronic illnesses — and they are poised to evolve the future of care. In this book, the authors explore the potential applications of a wave of sensor-based tools—including wearables and stand-alone devices for remote patient monitoring—and the marriage of internet-connected medical devices with patient information that ultimately sets the IoMT ecosystem apart. This book demonstrates the connectivity between medical devices and sensors is streamlining clinical workflow management and leading to an overall improvement in patient care, both inside care facilities and in remote locations.
This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.
Written by a range of researchers and practitioners in the field of IoT, data mining, and machine learning, this edited book provides a systemic review of trends, challenges and future directions of IoMT enabling technologies, such as machine learning, wireless communications, and network security.
SMART HEALTHCARE SYSTEM DESIGN This book deeply discusses the major challenges and issues for security and privacy aspects of smart health-care systems. The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security. The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies. Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations. Audience: Researchers and industry engineers in information technology, artificial intelligence, cyber security, as well as designers of healthcare systems, will find this book very valuable.
The COVID-19 epidemic has helped to expand the function of the Internet of Medical Things in healthcare at an exponential rate. This book offers a comprehensive exploration of IoMT in the post-COVID-19 era, providing an overview of modern technologies used for the improvement of healthcare, such as IoT, artificial intelligence, robotics, big data, and wearable devices used in healthcare applications, with a focus on the detection and treatment of COVID-19 and related viruses. The volume presents the principles, state-of-the-art developments, architecture, real-world applications, actual case studies, results of IoMT experiments and sensor-based systems, and more. The chapters look at various aspects of artificial intelligence in IoMT-based telemedicine, health monitoring, early COVID detection, automatic intravenous fluids feeds, chest x-ray images, data collection for decision-making, security of health information, and more. This volume provides an understanding of the real applications, development of healthcare systems, architectural frameworks, and modern design elements of healthcare systems.
