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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.
List of contents
Editors Biography xxi
List of Contributors xxiii
Preface xxxiii
1 Introduction 1
Giancarlo Fortino, David Kaber, Andreas Nürnberger, and David Mendonça
1.1 Book Rationale 1
1.2 Chapters Overview 2
Acknowledgments 8
References 8
2 Brain-Computer Interfaces: Recent Advances, Challenges, and Future Directions 11
Tiago H. Falk, Christoph Guger, and Ivan Volosyak
2.1 Introduction 11
2.2 Background 12
2.2.1 Active/Reactive BCIs 13
2.2.2 Passive BCIs 14
2.2.3 Hybrid BCIs 15
2.3 Recent Advances and Applications 15
2.3.1 Active/Reactive BCIs 15
2.3.2 Passive BCIs 16
2.3.3 Hybrid BCIs 16
2.4 Future Research Challenges 16
2.4.1 Current Research Issues 17
2.4.2 Future Research Directions 17
2.5 Conclusions 18
References 18
3 Brain-Computer Interfaces for Affective Neurofeedback Applications 23
Lucas R. Trambaiolli and Tiago H. Falk
3.1 Introduction 23
3.2 Background 23
3.3 State-of-the-Art 24
3.3.1 Depressive Disorder 25
3.3.2 Posttraumatic Stress Disorder, PTSD 26
3.4 Future Research Challenges 27
3.4.1 Open Challenges 27
3.4.2 Future Directions 28
3.5 Conclusion 28
References 29
4 Pediatric Brain-Computer Interfaces: An Unmet Need 35
Eli Kinney-Lang, Erica D. Floreani, Niloufaralsadat Hashemi, Dion Kelly, Stefanie S. Bradley, Christine Horner, Brian Irvine, Zeanna Jadavji, Danette Rowley, Ilyas Sadybekov, Si Long Jenny Tou, Ephrem Zewdie, Tom Chau, and Adam Kirton
4.1 Introduction 35
4.1.1 Motivation 36
4.2 Background 36
4.2.1 Components of a BCI 36
4.2.1.1 Signal Acquisition 36
4.2.1.2 Signal Processing 36
4.2.1.3 Feedback 36
4.2.1.4 Paradigms 37
4.2.2 Brain Anatomy and Physiology 37
4.2.3 Developmental Neurophysiology 38
4.2.4 Clinical Translation of BCI 38
4.2.4.1 Assistive Technology (AT) 38
4.2.4.2 Clinical Assessment 39
4.3 Current Body of Knowledge 39
4.4 Considerations for Pediatric BCI 40
4.4.1 Developmental Impact on EEG-based BCI 40
4.4.2 Hardware for Pediatric BCI 41
4.4.3 Signal Processing for Pediatric BCI 41
4.4.3.1 Feature Extraction, Selection and Classification 42
4.4.3.2 Emerging Techniques 42
4.4.4 Designing Experiments for Pediatric BCI 43
4.4.5 Meaningful Applications for Pediatric BCI 43
4.4.6 Clinical Translation of Pediatric BCI 44
4.5 Conclusions 44
References 45
5 Brain-Computer Interface-based Predator-Prey Drone Interactions 49
Abdelkader Nasreddine Belkacem and Abderrahmane Lakas
5.1 Introduction 49
5.2 Related Work 50
5.3 Predator-Prey Drone Interaction 51
5.4 Conclusion and Future Challenges 57
References 58
6 Levels of Cooperation in Human-Machine Systems: A Human-BCI-Robot Example 61
Marie-Pierre Pacaux-Lemoine, Lydia Habib, and Tom Carlson
6.1 Introduction 61
6.2 Levels of Cooperation 61
6.3 Application to the Control of a Robot by Thought 63
6.3.1 Designing the System 64
6.3.2 Experiments and Results 66
6.4 Results from the Methodological Point of View 67
6.5 Conclusion and Perspectives 68
References 69
7 Human-Machine Social Systems: Test and Validation via Military Use Cases 71
Charlene K. Stokes, Monika Lohani, Arwen H. D
About the author
Giancarlo Fortino, PhD, is a Full Professor of Computer Engineering, Chair of the ICT PhD School, and Rector's Delegate for International Relations with the Department of Informatics, Modeling, Electronics, and Systems at University of Calabria, Italy.
David Kaber, PhD, is the Department Chair and Dean's Leadership Professor with the Department of Industrial & Systems Engineering at the University of Florida.
Andreas Nürnberger, PhD, is a Full Professor for Data and Knowledge Engineering in the Faculty of Computer Science at Otto-von-Guericke-Universität Magdeburg, Germany.
David Mendonça, PhD, is a Senior Principal Decision Scientist at Advanced Software Innovation.
Summary
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.
