The Handbook of Human-Machine Interaction features 20 original chapters and a conclusion focusing on human-machine interaction (HMI) from analysis, design and evaluation perspectives. It offers a comprehensive range of principles, methods, techniques and tools to provide the reader with a clear knowledge of the current academic and industry practice and debate that define the field. The text considers physical, cognitive, social and emotional aspects and is illustrated by key application domains such as aerospace, automotive, medicine and defence. Above all, this volume is designed as a research guide that will both inform readers on the basics of human-machine interaction from academic and industrial perspectives and also provide a view ahead at the means through which human-centered designers, including engineers and human factors specialists, will attempt to design and develop human-machine systems.

Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of "shared contexts between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines. This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts by reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these "machines" may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared by users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers "think through this change in human terms," the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers. - Discusses the foundations, metrics, and applications of human-machine systems - Considers advances and challenges in the performance of autonomous machines and teams of humans - Debates theoretical human-machine ecosystem models and what happens when machines malfunction

HUMAN-MACHINE INTERFACE The book contains the latest advances in healthcare and presents them in the frame of the Human-Machine Interface (HMI). The Human-Machine Interface (HMI) industry has witnessed the evolution from a simple push button to a modern touch-screen display. HMI is a user interface that allows humans to operate controllers for machines, systems, or instruments. Most medical procedures are improved by HMI systems, from calling an ambulance to ensuring that a patient receives adequate treatment on time. This book describes the scenario of biomedical technologies in the context of the advanced HMI, with a focus on direct brain-computer connection. The book describes several HMI tools and related techniques for analyzing, creating, controlling, and upgrading healthcare delivery systems, and provides details regarding how advancements in technology, particularly HMI, ensure ethical and fair use in patient care. Audience The target audience for this book is medical personnel and policymakers in healthcare and pharmaceutical professionals, as well as engineers and researchers in computer science and artificial intelligence.

Publisher description

Human-Machine Systems Design and Evaluation Methodology for Intelligent Vehicles examines the fields of designing and developing intelligent design and intelligent vehicle driving evaluation by using virtual reality, augmented reality, and other technologies. The book explains the methodologies and systems of interactive design, user evaluation and testing using virtual reality technology and augmented reality technology in intelligent cockpit design. With the rising prominence of electric vehicles and automatic driving (assisted) technology, intelligent vehicles are becoming a reality. Compared to traditional interactive design, artificial intelligence provides new opportunities and challenges for the interactive design of intelligent cockpit space, especially under the condition of intelligent assisted driving, the driver's behavior performance, multimodal interactive display interface design and evaluation. - Focuses on the interactive design methods of intelligent vehicles, as well as forward-looking design and testing methods of intelligent vehicle design - Emphasizes that interactive design should be carried out using the relevant elements of intelligent system in the design of intelligent cars: starting from the interactive characteristics of intelligence itself - Starts from AI interactive design and combines the field of cognitive science to develop the methods and technologies of vehicle borne equipment and collaborative human-computer interaction design - Includes design cases from the intelligent car interaction design laboratory of Tongji University and related scientific research projects in China.

This book constitutes the thoroughly refereed post-workshop proceedings of the Second Workshop on Multimodal Analyses Enabling Artificial Agents in Human Interaction, MA3HMI 2014, held in Conjunction with INTERSPEECH 2014, in Singapore, Singapore, on September 14th, 2014. The 9 revised papers presented together with a keynote talk were carefully reviewed and selected from numerous submissions. They are organized in two sections: human-machine interaction and dialogs and speech recognition.

This book, on the ergonomics of human−machine systems, is aimed at engineers specializing in informatics, automation, production or robotics, who are faced with a significant dilemma during the conception of human−machine systems. On the one hand, the human operator guarantees the reliability of the system and has been known to salvage numerous critical situations through an ability to reason in unplanned, imprecise and uncertain situations; on the other hand, the human operator can be unpredictable and create disturbances in the automated system. The first part of the book is dedicated to the methods of human-centered design, from three different points of view, the various chapters focusing on models developed by human engineers and functional models to explain human behavior in their environment, models of cognitive psychology and models in the domain of automobile driving. Part 2 develops the methods of evaluation of the human−machine systems, looking at the evaluation of the activity of the human operator at work and human error analysis methods. Finally, Part 3 is dedicated to human−machine cooperation, where the authors show that a cooperative agent comprises a know-how and a so-called know-how-to-cooperate and show the way to design and evaluate that cooperation in real industrial contexts.

Embodied conversational agents (ECA) and speech-based human-machine interfaces can together represent more advanced and more natural human-machine interaction. Fusion of both topics is a challenging agenda in research and production spheres. The important goal of human-machine interfaces is to provide content or functionality in the form of a dialo