Handbook of Human-Machine Systems

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Insightful and cutting-edge discussions of recent developments in human-machine systems InHandbook 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 Systemswill also earn a place in the libraries of technical professionals practicing in areas including computer science, artificial intelligence, cognitive science, engineering, psychology, and neurobiology.

Author(s): Fortino, Giancarlo;Kaber, David; Nürnberger, Andreas;Mendonça, David; David Kaber; Andreas Nürnberger; David Mendonça
Series: IEE Press Series on Human Machine Sysrtems
Publisher: Wiley
Year: 2023

Language: English
Pages: 528

Preface
1 Introduction
1.1 Book Rationale
1.2 Chapters Overview
Acknowledgments
References
2 Brain–Computer Interfaces: Recent Advances, Challenges, and Future Directions
2.1 Introduction
2.2 Background
2.3 Recent Advances and Applications
2.4 Future Research Challenges
2.5 Conclusions
References
3 Brain–Computer Interfaces for Affective Neurofeedback Applications
3.1 Introduction
3.2 Background
3.3 State-of-the-Art
3.4 Future Research Challenges
3.5 Conclusion
References
4 Pediatric Brain–Computer Interfaces: An Unmet Need
4.1 Introduction
4.2 Background
4.3 Current Body of Knowledge
4.4 Considerations for Pediatric BCI
4.5 Conclusions
References
Note
5 Brain–Computer Interface-based Predator–Prey Drone Interactions
5.1 Introduction
5.2 Related Work
5.3 Predator–Prey Drone Interaction
5.4 Conclusion and Future Challenges
References
6 Levels of Cooperation in Human–Machine Systems: A Human–BCI–Robot Example
6.1 Introduction
6.2 Levels of Cooperation
6.3 Application to the Control of a Robot by Thought
6.4 Results from the Methodological Point of View
6.5 Conclusion and Perspectives
References
7 Human–Machine Social Systems: Test and Validation via Military Use Cases
7.1 Introduction
7.2 Background Summary: From Tools to Teammates
7.3 Future Research Directions
7.4 Conclusion
References
8 The Role of Multimodal Data for Modeling Communication in Artificial Social Agents
8.1 Introduction
8.2 Background
8.3 Related Work
8.4 Datasets and Resulting Implications
8.5 Conclusions
8.6 Future Research Challenges
References
Notes
9 Modeling Interactions Happening in People-Driven Collaborative Processes
9.1 Introduction
9.2 Background
9.3 State-of-the-Art in Interaction Modeling Languages and Notations
9.4 Challenges and Future Research Directions
References
10 Transparent Communications for Human–Machine Teaming
10.1 Introduction
10.2 Definitions and Frameworks
10.3 Implementation of Transparent Human–Machine Interfaces in Intelligent Systems
10.4 Future Research Directions
References
11 Conversational Human–Machine Interfaces
11.1 Introduction
11.2 Background
11.3 State-of-the-Art
11.4 Future Research Challenges
References
Notes
12 Interaction-Centered Design: An Enduring Strategy and Methodology for Sociotechnical Systems
12.1 Introduction
12.2 Evolution of HMS Design Strategy
12.3 State-of-the-Art: Interaction-Centered Design
12.4 IAS Design Challenges and Future Work
References
13 Human–Machine Computing: Paradigm, Challenges, and Practices
13.1 Introduction
13.2 Background
13.3 State of the Art
13.4 Future Research Challenges
References
14 Companion Technology
14.1 Introduction
14.2 Background
14.3 State-of-the-Art
14.4 Future Research Challenges
References
Note
15 A Survey on Rollator-Type Mobility Assistance Robots
15.1 Introduction
15.2 Mobility Assistance Platforms
15.3 Functionalities
15.4 Conclusion
References
16 A Wearable Affective Robot
16.1 Introduction
16.2 Architecture Design and Characteristics
16.3 Design of the Wearable, Affective Robot's Hardware
16.4 Algorithm for the Wearable Affective Robot
16.5 Life Modeling of the Wearable Affective Robot
16.6 Challenges and Prospects
16.7 Conclusions
References
17 Visual Human–Computer Interactions for Intelligent Vehicles
17.1 Introduction
17.2 Background
17.3 State-of-the-Art
17.4 Future Research Challenges
References
18 Intelligent Collaboration Between Humans and Robots
18.1 Introduction
18.2 Background
18.3 Related Work
18.4 Validation Cases
18.5 Conclusions
18.6 Future Research Challenges
References
Notes
19 To Be Trustworthy and To Trust: The New Frontier of Intelligent Systems
19.1 Introduction
19.2 Background
19.3 Basic Definitions
19.4 State-of-the-Art
19.5 Future Research Challenges
References
20 Decoding Humans' and Virtual Agents' Emotional Expressions
20.1 Introduction
20.2 Related Work
20.3 Materials and Methodology
20.4 Descriptive Statistics
20.5 Data Analysis and Results
20.6 Discussion and Conclusions
Acknowledgment
References
21 Intelligent Computational Edge: From Pervasive Computing and Internet of Things to Computing Continuum
21.1 Introduction
21.2 The Journey of Pervasive Computing
21.3 The Power of the IoT
21.4 IoT: The Journey from Cloud to Edge
21.5 Toward Intelligent Computational Edge
21.6 Is Computing Continuum the Answer?
21.7 Do We Have More Questions than Answers?
21.8 What Would our Vision Be?
References
22 Implementing Context Awareness in Autonomous Vehicles
22.1 Introduction
22.2 Background
22.3 Related Works
22.4 Implementation and Tests
22.5 Conclusions
22.6 Future Research Challenges
References
Notes
23 The Augmented Workforce: A Systematic Review of Operator Assistance Systems
23.1 Introduction
23.2 Background
23.3 State of the Art
23.4 Future Research Directions
23.5 Conclusion
References
24 Cognitive Performance Modeling
24.1 Introduction
24.2 Background
24.3 State-of-the-Art
24.4 Current Research Issues
24.5 Future Research Directions Dealing with the Current Issues
References
25 Advanced Driver Assistance Systems: Transparency and Driver Performance Effects
25.1 Introduction
25.2 Background
25.3 Related Work
25.4 Method
25.5 Results
25.6 Discussion
25.7 Conclusion
25.8 Future Research
References
26 RGB-D Based Human Action Recognition: From Handcrafted to Deep Learning
26.1 Introduction
26.2 RGB-D Sensors and 3D Data
26.3 Human Action Recognition via Handcrafted Methods
26.4 Human Action Recognition via Deep Learning Methods
26.5 Discussion
26.6 RGB-D Datasets
26.7 Conclusion and Future Directions
References
27 Hybrid Intelligence: Augmenting Employees' Decision-Making with AI-Based Applications
27.1 Introduction
27.2 Background
27.3 Related Work
27.4 Technical Part of the Chapter
27.5 Conclusions
27.6 Future Research Challenges
References
28 Human Factors in Driving
28.1 Introduction
28.2 Research Methodologies
28.3 In-Vehicle Electronic Devices
28.4 Vehicle Automation
28.5 Driver Monitoring Systems
28.6 Conclusion
References
29 Wearable Computing Systems: State-of-the-Art and Research Challenges
29.1 Introduction
29.2 Wearable Devices
29.3 Body Sensor Networks-based Wearable Computing Systems
29.4 Applications of Wearable Devices and BSNs
29.5 Challenges and Prospects
29.6 Conclusions
Acknowledgment
References
30 Multisensor Wearable Device for Monitoring Vital Signs and Physical Activity
30.1 Introduction
30.2 Background
30.3 Related Work
30.4 Case Study: Multisensor Wearable Device for Monitoring RR and Physical Activity
30.5 Conclusions
30.6 Future Research Challenges
References
Notes
31 Integration of Machine Learning with Wearable Technologies
31.1 Introduction
31.2 Background
31.3 State of the Art
31.4 Future Research Challenges
References
Note
32 Gesture-Based Computing
32.1 Introduction
32.2 Background
32.3 State of the Art
32.4 Future Research Challenges
Acknowledgment
References
Note
33 EEG-based Affective Computing
33.1 Introduction
33.2 Background
33.3 State-of-the-Art
33.4 Challenges and Future Directions
Acknowledgment
References
34 Security of Human Machine Systems
34.1 Introduction
34.2 Background
34.3 State of the Art
34.4 Conclusions and Future Research
References
Notes
35 Integrating Innovation: The Role of Standards in Promoting Responsible Development of Human–Machine Systems
35.1 Introduction to Standards in Human–Machine Systems
35.2 The HMS Standards Landscape
35.3 Standards Development Process
35.4 Strategic Considerations and Discussion
Acknowledgments
References
36 Situation Awareness in Human-Machine Systems
36.1 Introduction
36.2 Background
36.3 State-of-the-Art
36.4 Discussion and Research Challenges
36.5 Conclusion
References
37 Modeling, Analyzing, and Fostering the Adoption of New Technologies: The Case of Electric Vehicles
37.1 Introduction
37.2 Background
37.3 Fostering the EV Transition via Control over Networks
37.4 Boosting EV Adoption with Feedback
37.5 Experimental Results
37.6 Conclusions
37.7 Future Research Challenges
Acknowledgments
References
Notes
Index
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