Handbook of Human Machine Systems IEEE Press Series on Human Machine Systems 1st Edition by Giancarlo Fortino,David Kaber,Andreas Nurnberger,David Mendonca ISBN 1119863635 978-1119863632

Handbook of Human-Machine Systems (IEEE Press Series on Human-Machine Systems) 1st Edition by Giancarlo Fortino, David Kaber, Andreas Nürnberger, David Mendonça – Ebook PDF Instant Download/Delivery: 1119863635, 978-1119863632

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Product details:

ISBN 10: 1119863635 

ISBN 13: 978-1119863632

Author: Giancarlo Fortino, David Kaber, Andreas Nürnberger, David Mendonça

Handbook of Human-Machine Systems

Insightful and cutting-edge discussions of recent developments in human-machine systems

In Handbook of Human-Machine Systems, a team of distinguished researchers delivers a comprehensive exploration of human-machine systems (HMS) research and development from a variety of illuminating perspectives. The book offers a big picture look at state-of-the-art research and technology in the area of HMS. Contributing authors cover Brain-Machine Interfaces and Systems, including assistive technologies like devices used to improve locomotion. They also discuss advances in the scientific and engineering foundations of Collaborative Intelligent Systems and Applications.

Companion technology, which combines trans-disciplinary research in fields like computer science, AI, and cognitive science, is explored alongside the applications of human cognition in intelligent and artificially intelligent system designs, human factors engineering, and various aspects of interactive and wearable computers and systems. The book also includes:

• A thorough introduction to human-machine systems via the use of emblematic use cases, as well as discussions of potential future research challenges
• Comprehensive explorations of hybrid technologies, which focus on transversal aspects of human-machine systems
• Practical discussions of human-machine cooperation principles and methods for the design and evaluation of a brain-computer interface

Perfect for academic and technical researchers with an interest in HMS, Handbook of Human-Machine Systems will also earn a place in the libraries of technical professionals practicing in areas including computer science, artificial intelligence, cognitive science, engineering, psychology, and neurobiology.

Table of contents:

1.  
   

   1. Introduction

   2. Brain–Computer Interfaces: Recent Advances, Challenges, and Future Directions

   3. Brain–Computer Interfaces for Affective Neurofeedback Applications

   4. Pediatric Brain–Computer Interfaces: An Unmet Need

   5. Brain–Computer Interface-based Predator–Prey Drone Interactions

   6. Levels of Cooperation in Human–Machine Systems: A Human–BCI–Robot Example

   7. Human–Machine Social Systems: Test and Validation via Military Use Cases

   8. The Role of Multimodal Data for Modeling Communication in Artificial Social Agents

   9. Modeling Interactions Happening in People-Driven Collaborative Processes

   10. Transparent Communications for Human–Machine Teaming

   11. Conversational Human–Machine Interfaces

   12. Interaction-Centered Design: An Enduring Strategy and Methodology for Sociotechnical Systems

   13. Human–Machine Computing: Paradigm, Challenges, and Practices

   14. Companion Technology

   15. A Survey on Rollator-Type Mobility Assistance Robots

   16. A Wearable Affective Robot

   17. Visual Human–Computer Interactions for Intelligent Vehicles

   18. Intelligent Collaboration Between Humans and Robots

   19. To Be Trustworthy and To Trust: The New Frontier of Intelligent Systems

   20. Decoding Humans’ and Virtual Agents’ Emotional Expressions

   21. Intelligent Computational Edge: From Pervasive Computing and Internet of Things to Computing Continuum

   22. Implementing Context Awareness in Autonomous Vehicles

   23. The Augmented Workforce: A Systematic Review of Operator Assistance Systems

   24. Cognitive Performance Modeling

   25. Advanced Driver Assistance Systems: Transparency and Driver Performance Effects

   26. RGB-D Based Human Action Recognition: From Handcrafted to Deep Learning

   27. Hybrid Intelligence: Augmenting Employees’ Decision-Making with AI-Based Applications

   28. Human Factors in Driving

   29. Wearable Computing Systems: State-of-the-Art and Research Challenges

   30. Multisensor Wearable Device for Monitoring Vital Signs and Physical Activity

   31. Integration of Machine Learning with Wearable Technologies

   32. Gesture-Based Computing

   33. EEG-based Affective Computing

   34. Security of Human Machine Systems

   35. Integrating Innovation: The Role of Standards in Promoting Responsible Development of Human–Machine Systems

    

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Tags: Giancarlo Fortino, David Kaber, Andreas Nurnberger, David Mendonca, Handbook of Human, Machine Systems, IEEE Press Series on Human