Modern Intervention Tools for Rehabilitation addresses current advancements in rehabilitation to better equip clinicians and researchers in the field. This resource will equip professionals for better patient outcomes and improve future rehabilitation research quality. An interdisciplinary understanding of the rehabilitation field is crucial for improved patient care and outcomes, with relevance to patient care in other disciplines as well. With chapters dedicated to diagnostics, choosing appropriate techniques, managing medical treatment, and proper equipment care, readers will be well-equipped to decide on protocols, increase patient outcomes, and improve quality of life.

Smart Healthcare for Disease Diagnosis and Prevention focuses on the advancement in healthcare technology to improve human health at all levels using smart technologies. It covers all necessary topics from basic concepts (such as signal and image processing) to advanced knowledge on topics such as tissue engineering, virtual and intelligent instrumentation (or VLSI) and Embedded Systems. This book can be used to guide students and young researchers, providing basic knowledge on signal/image processing and smart technologies. Users will find a perfect blend of the interdisciplinary approach to biomedical engineering. The book considers many technical concepts, emerging technologies, real-world healthcare applications, and many other technical, multidisciplinary notions in the same content. Finally, it systemically introduces the technologies and devices for healthcare objects and targets disease diagnosis and prevention in different views.

This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.

This book is a compilation of work by experts from the different domains of the healthcare industry, ranging from hospital planning to quality management, clinical services to disaster management.Healthcare organizations, being diverse, sensitive, and intricate, warrant thorough and flawless planning. The structure should be not only operationally efficient but also safe for its occupants and visitors. It starts with a brief introduction of the healthcare sector at different levels. It also attempts to justify how the changing healthcare landscape paved the way for establishing a contemporary and ever-evolving specialty of Hospital planning and designing, which is dynamic and frequently requires continuous improvements and updates. Clinical and non-clinical departments have been separately classified in this book, and their respective standards and guidelines have been incorporated while describing the planning concepts. Critical areas of a hospital such as ICU, CCU have been detailed precisely as the operational requirements and level of different sophistication required. A chapter on security aspects and disaster management has also been thoroughly envisioned based on the current scenario at the global level. Issues and management of Hospital Acquired Infection are explained in different chapters based on its relevance and application in that particular area.