What is artificial intelligence (AI)? What is healthcare robotics? How can AI and healthcare robotics assist in contemporary medicine? Robotics and AI can offer society unimaginable benefits, such as enabling wheelchair users to walk again, performing surgery in a highly automated and minimally invasive way, and delivering care more efficiently. AI for Healthcare Robotics explains what healthcare robots are and how AI empowers them in achieving the goals of contemporary medicine.

This book provides a thorough background to the emerging field of medical robotics. It covers the mathematics needed to understand the use of robotic devices in medicine, including but not limited to robot kinematics, hand-eye and robot-world calibration, reconstruction, registration, motion planning, motion prediction, motion correlation, motion replication and motion learning. Additionally, basic methods behind state-of-the art robots like the DaVinci system, the CyberKnife, motorized C-arms and operating microscopes as well as stereotactic frames are presented. The book is a text book for undergraduates in computer science and engineering. The main idea of the book is to motivate the methods in robotics in medical applications rather than industrial applications. The book then follows the standard path for a robotics textbook. It is thus suitable for a first course in robotics for undergraduates. It is the first textbook on medical robotics.

The work is a collection of contributions resulting from R&D efforts originated from scientific projects involving academia, technological partners, and end-user institutions. The aim is to provide a comprehensive overview of robotics technology applied to Healthcare, and discuss the anticipation of upcoming challenges. The intersection of Robotics and Medicine includes socially and economically relevant areas, such as rehabilitation, therapy, and healthcare. Innovative usages of current robotics technologies are being somewhat stranded by concerns related to social dynamics. The examples covered in this volume show some of the potential societal benefits robotics can bring and how the robots are being integrated in social environments. Despite the aforementioned concerns, a fantastic range of possibilities is being opened. The current trend in social robotics adds to technology challenges and requires R&D to think about Robotics as an horizontal discipline, intersecting social and exact sciences. For example, robots that can act as if they have credible personalities (not necessarily similar to humans) living in social scenarios, eventually helping people. Also, robots can move inside the human body to retrieve information that otherwise is difficult to obtain. The decision autonomy of these robots raises a broad range of subjects though the immediate advantages of its use are evident. The book presents examples of robotics technologies tested in healthcare environments or realistically close to being deployed in the field and discusses the challenges involved. Chapter 1 provides a comprehensive overview of Healthcare robotics and points to realistically expectable developments in the near future. Chapter 2 describes the challenges deploying a social robot in the Pediatrics ward of an Oncological hospital for simple edutainment activities. Chapter 3 focuses on Human-Robot Interaction techniques and their role in social robotics. Chapter 4 focus on R&D efforts behind an endoscopic capsule robot. Chapter 5 addresses experiments in rehabilitation with orthotics and walker robots. These examples have deep social and economic relations with the Healthcare field, and, at the same time, are representative of the R&D efforts the robotics community is developing.

The integration of robotic systems and artificial intelligence into healthcare settings is accelerating. As these technological developments interact socially with children, the elderly, or the disabled, they may raise concerns besides mere physical safety; concerns that include data protection, inappropriate use of emotions, invasion of privacy, autonomy suppression, decrease in human interaction, and cognitive safety. Given the novelty of these technologies and the uncertainties surrounding the impact of care automation, it is unclear how the law should respond. This book investigates the legal and regulatory implications of the growing use of personal care robots for healthcare purposes. It explores the interplay between various aspects of the law, including safety, data protection, responsibility, transparency, autonomy, and dignity; and it examines different robotic and AI systems, such as social therapy robots, physical assistant robots for rehabilitation, and wheeled passenger carriers. Highlighting specific problems and challenges in regulating complex cyber-physical systems in concrete healthcare applications, it critically assesses the adequacy of current industry standards and emerging regulatory initiatives for robots and AI. After analyzing the potential legal and ethical issues associated with personal care robots, it concludes that the primarily principle-based approach of recent law and robotics studies is too abstract to be as effective as required by the personal care context. Instead, it recommends bridging the gap between general legal principles and their applicability in concrete robotic and AI technologies with a risk-based approach using impact assessments. As the first book to compile both legal and regulatory aspects of personal care robots, this book will be a valuable addition to the literature on robotics, artificial intelligence, human–robot interaction, law, and philosophy of technology.

This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019. The conference attracted a total of 371 submissions from pioneering researchers, scientists, industrial engineers, and students all around the world. These submissions underwent a double-blind peer review process, after which 120 (including 7 poster papers) were selected for inclusion in these proceedings. The book's goal is to reflect the intellectual breadth and depth of current research on computer vision, from classical to intelligent scope. Accordingly, its respective chapters address state-of-the-art intelligent methods and techniques for solving real-world problems, while also outlining future research directions. Topic areas covered include Machine Vision and Learning, Data Science, Image Processing, Deep Learning, and Computer Vision Applications.

Lays a good foundation for robotics' core concepts and principles in biomedical and healthcare engineering, walking the reader through the fundamental ideas with expert ease. Progresses on the topics in a step-by-step manner and reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into its applications. Features chapters that introduce and cover novel ideas in healthcare engineering like Applications of Robots in Surgery, Microrobots and Nanorobots in Healthcare Practices, Intelligent walker for posture monitoring, AI-Powered Robots in Biomedical and Hybrid Intelligent System for Medical Diagnosis, etc.

This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions. This book features a wide range of topics such as AI techniques, IoT, cloud, wearables, and secured data transmission. Written for a broad audience, this book will be useful for clinicians, health professionals, engineers, technology developers, IT consultants, researchers, and students interested in the AI-based healthcare applications. Provides a deeper understanding of key AI algorithms and their use and implementation within the wider healthcare sector Explores different disease diagnosis models using machine learning, deep learning, healthcare data analysis, including machine learning, and data mining and soft computing algorithms Discusses detailed IoT, wearables, and cloud-based disease diagnosis model for intelligent systems and healthcare Reviews different applications and challenges across the design, implementation, and management of intelligent systems and healthcare data networks Introduces a new applications and case studies across all areas of AI in healthcare data K. Shankar (Member, IEEE) is a Postdoctoral Fellow of the Department of Computer Applications, Alagappa University, Karaikudi, India. Eswaran Perumal is an Assistant Professor of the Department of Computer Applications, Alagappa University, Karaikudi, India. Dr. Deepak Gupta is an Assistant Professor of the Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.