Remote Patient Monitoring A Computational Perspective In Healthcare

This book provides a multidisciplinary overview of the design and implementation of systems for remote patient monitoring and healthcare. Readers are guided through the components of such a system and shown how they could be integrated into a coherent framework for deployment in practice. The book ends with a discussion of case studies to provide practical examples and design methods for remote healthcare systems with different needs. This book contains information that will be helpful to undergraduate and postgraduate students, academic and professional researchers, and individuals who employ computational intelligence. By presenting new models of care and support, AI in medicine is having an impact on the entire value chain of clinical practice and the patient care delivery system. This is especially evident in telemedicine breakthroughs, where applications of AI are utilized to assist, complement, or create new forms of remote healthcare. Through the use of communications technology, telemedicine enables medical professionals to examine, diagnose, and treat patients remotely. Now, the technology might also integrate online diagnostics, etc., to increase the effectiveness of the healthcare system and enhance patient outcomes. By enabling elderly people to live independently, technological advancements in fields like remote patient monitoring (RPM) systems can revolutionize senior care. Medical diagnosis will improve, and remote patient monitoring will become simpler thanks to artificial intelligence. The resistance of many patients and doctors to using the telemedicine idea for medical visits will probably be overcome by AI automation.

This book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, machine learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data-driven approach is not taken. With the help of computing systems, today, it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, computing techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of genomic data using various computing techniques is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which machine learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression.

This book gives an overview of innovative approaches in telehealth and telemedicine. The Goal of the content is to inform readers about recent computer applications in e-health, including Internet of Things (IoT) and Internet of Medical Things (IoMT) technology. The 9 chapters will guide readers to determine the urgency to intervene in specific medical cases, and to assess risk to healthcare workers. The focus on telehealth along with telemedicine, encompasses a broader spectrum of remote healthcare services for the reader to understand. Chapters cover the following topics: - A COVID-19 care system for virus precaution, prevention, and treatment - The Internet of Things (IoT) in Telemedicine, - Artificial Intelligence for Remote Patient Monitoring systems - Machine Learning in Telemedicine - Convolutional Neural Networks for the detection and prediction of melanoma in skin lesions - COVID-19 virus contact tracing via mobile apps - IoT and Cloud convergence in healthcare - Lung cancer classification and detection using deep learning - Telemedicine in India This book will assist students, academics, and medical professionals in learning about cutting-edge telemedicine technologies. It will also inform beginner researchers in medicine about upcoming trends, problems, and future research paths in telehealth and telemedicine for infectious disease control and cancer diagnosis.

This book provides in depth knowledge about critical factors involved in the success of pervasive healthcare. The book first presents critical components and importance of pervasive healthcare. The authors then give insight into the pervasive healthcare information systems and key consideration related to remote patient monitoring and safety. The book provides in-depth discussion about the security issues and protocols for pervasive healthcare. This book explores concepts and techniques behind the successive pervasive healthcare systems by providing in-depth knowledge about patient empowerment, remote patient monitoring, network establishment and protocols for effective pervasive healthcare. The book also provides case studies in the field. It is an ideal resource for researchers, students and healthcare organizations to get insight about the state of the art in pervasive healthcare systems. Provides current research, developments, and applications in pervasive healthcare; Includes technologies such as machine learning, cryptography, fog computing, and big data in the advancement of e-healthcare; Pertinent for researchers, students, practitioners and healthcare decision makers.

Different healthcare technologies have been in use for decades. These technologies are continuously evolving and changing the way medicine will be practiced in the future. These technologies allow medical practice from anywhere, at any time, and from any device. These technologies are mainly concerned with the resources, devices, and methods required to optimize the acquisition, storage, retrieval, processing, and use of information in health. Recent Advancements in Smart Remote Patient Monitoring, Wearable Devices, and Diagnostics Systems provides relevant theoretical and practical frameworks, as well as the latest empirical research findings in the area. It provides insights and supports executives concerned with remote patient monitoring through wearable devices and diagnostics systems. Covering topics such as cloud computing, obesity monitoring systems, and photoacoustic imaging, this premier reference source is an essential resource for hospital administrators, medical technicians, healthcare professionals, medical students and educators, librarians, researchers, and academicians.

To overcome the constraints of 5G for supporting new challenges, 6G wireless systems must be developed with new and attractive features. These systems are expected to increase performance and maximize quality of service several folds more than 5G along with other exciting features. However, 6G is still in its infancy and must be explored. The Handbook of Research on Design, Deployment, Automation, and Testing Strategies for 6G Mobile Core Network discusses the technological feats used in the new 6G wireless systems. It discusses the design, automation, and uses for industry as well as testing strategies. Covering topics such as 6G architecture, smart healthcare, and wireless communication, this major reference work is an excellent resource for computer scientists, engineers, students and professors in higher education, researchers, and academicians.

Wearable Telemedicine Technology for the Healthcare Industry: Product Design and Development focuses on recent advances and benefits of wearable telemedicine techniques for remote health monitoring and prevention of chronic conditions, providing real time feedback and help with rehabilitation and biomedical applications. Readers will learn about various techniques used by software engineers, computer scientists and biomedical engineers to apply intelligent systems, artificial intelligence, machine learning, virtual reality and augmented reality to gather, transmit, analyze and deliver real-time clinical and biological data to clinicians, patients and researchers. Wearable telemedicine technology is currently establishing its place with large-scale impact in many healthcare sectors because information about patient health conditions can be gathered anytime and anywhere outside of traditional clinical settings, hence saving time, money and even lives. Provides readers with methods and applications for wearable devices for ubiquitous health and activity monitoring, wearable biosensors, wearable app development and management using machine learning techniques, and more Integrates coverage of a number of key wearable technologies, such as ubiquitous textile systems for movement disorders, remote surgery using telemedicine, intelligent computing algorithms for smart wearable healthcare devices, blockchain, and more Provides readers with in-depth coverage of wearable product design and development

This book provides a multidisciplinary overview of the design and implementation of systems for remote patient monitoring and healthcare. Readers are guided step-by-step through the components of such a system and shown how they could be integrated in a coherent framework for deployment in practice. The authors explain planning from subsystem design to complete integration and deployment, given particular application constraints. Readers will benefit from descriptions of the clinical requirements underpinning the entire application scenario, physiological parameter sensing techniques, information processing approaches and overall, application dependent system integration. Each chapter ends with a discussion of practical design challenges and two case studies are included to provide practical examples and design methods for two remote healthcare systems with different needs.