Neuroergonomics

  • ID: 4482921
  • Book
  • 250 Pages
  • Elsevier Science and Technology
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Neuroergonomics: The Brain at Work and in Everyday Life details the methodologies that are useful for keeping an ideal human-machine system up-to-date, along with information on how to prevent potential overload and minimize errors. It discusses neural measures and the proper methods and technologies to maximize performance, thus providing a resource for neuroscientists who want to learn more about the technologies and real-time tools that can help them assess cognitive and motivational states of human operators and close the loop for advanced human-machine interaction.

With the advent of new and improved tools that allow monitoring of brain activity in the field and better identification of neurophysiological markers that can index impending overload or fatigue, this book is a timely resource on the topic.

  • Includes neurobiological models to better understand risky decision-making and cognitive countermeasures, augmented cognition, and brain stimulations to enhance performance and mitigate human error
  • Features innovative methodologies and protocols using psychophysiological measurements and brain imaging techniques in realistic operational settings
  • Discusses numerous topics, including cognitive performance in psychological and neurological disorders, brain computer interfaces (BCI), and human performance monitoring in ecological conditions, virtual reality, and serious gaming
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Introduction 1. Progress and Direction in Neuroergonomics

Methods 2. Electroencephelography for Neuroergonomics 3. Functional Near Infrared Spectroscopy for Neuroergonomics 4. Why is eye-tracking an essential part of Neuroergonomics? 5. The use of tDCS and rTMS methods in Neuroergonomics 6. Brain Computer Interfaces for Neuroergonomics 7. Transcranial Doppler Sonography for Neuroergonomics 8. Simulators and Behavioral Research Methods for Neuroergonomics 9. Neuroergonomics for Aviation 10. MoBI
Mobile Brain Body Imaging 11. Experiments with participants: Some ethical considerations

Neuroadaptive Interfaces and Operator Assessment 12. Measuring the Redline for Mental Overload Using EEG and fNIRS: A Role for Neural Efficiency? 13. Drowsiness Detection during Driving Task Using fNIRS 14. Neuroergonomic Multimodal Neuroimaging During a Simulated Aviation Pursuit Task 15. Is Mindfulness Helping the Brain to Drive? 16. Tracking Team Mental Workload by Multimodal Measurements in The Operating Room 17. Towards Brain-Based Interaction Between Humans and Technology: Does Age Matter? 18. Curvilinear Basis for Cognitive Load State Classification 19. Computational Models for Near Real-Time Performance Predictions Based on Physiological Measures of Workload 20. Mental Workload Assessment as Taxonomic Tool for Neuroergonomics 21. Preliminary Validation of an Adaptive Tactical Training Model: Cognitive Alignment with Performance Targeted Training Intervention Model

Neurostimulation Applications 22. Concurrent fNIRS and TMS for Neurocognitive Enhancement on a Speed of Processing Task 23. Neuromodulatory Effects of Transcranial Direct Current Stimulation Revealed by Functional Magnetic Resonance Imaging 24. Neurophysiological Correlates of tDCS-induced Modulation of Cortical Sensorimotor Networks: A Simultaneous fNIRS-EEG study 25. The use of Online/Offline Terminology for Transcranial Direct Current

Emerging Applications in Decision-making, Usability, Trust and Emotions 26. Neural Signatures of Advice Utilization During Human-Machine Agent Interactions: Functional Magnetic Resonance Imaging and Effective Connectivity Evidence 27. Psychophysical Equivalence of Static Versus Dynamic Stimuli in a Two Alternative Forced Choice Detection Task 28. Functional Near Infrared Spectroscopy: Proof of Concept for its Application in Social Neuroscience 29. Quantifying Brain Hemodynamics during Neuromuscular Fatigue 30. The Assessment of Emotions and Decision Making in Everyday Living Using fNIRS 31. Web Usability Testing with Concurrent fNIRS and Eye Tracking 32. Hybrid Collaborative Brain-Computer Interfaces to Augment Group Decision Making 33. How to Recognize Emotion Without Signal Processing: An Application of Convolutional Neural Network to Physiological Signals

Entries from the Inaugural International Neuroergonomics Conference

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Ayaz, Hasan
Dr. Ayaz is an Associate Research Professor of Biomedical Engineering at Drexel University, Philadelphia, PA with adjunct appointments at the University of Pennsylvania and the Children's Hospital of Philadelphia. Since 2001, he has worked on the development of continuous wave functional near infrared sensors and developed enabling software for brain monitoring instruments that were licensed by fNIR Devices LLC and distributed globally by Biopac Systems, Inc. As an extension to this, he led the software design and development for a portable-handheld medical device (Infrascanner) that utilizes fNIR to detect hematoma in head trauma patients, which received FDA approval and is currently being distributed in three continents for emergency care and pre-hospitalization screening. Dr. Ayaz's research interests include neuroengineering applications of human computer interaction and Neuroergonomics. His research activities with optical brain imaging focus on human computer interaction, neuroergonomics, and brain computer interface both in the field and in clinical applications. With 90+ publications in international journals and conferences, his research has been funded by federal agencies including the Department of Defence, FAA, and NIH, corporate partners Lockheed Martin Corporation and Intel Corporation, and has managed multi-institutional research and development projects
Dehais, Frederic
Dr. Dehais is a full professor at the Institut Supérieur de l'Aéronautique et de l'Espace (France) and the AXA Chair in Neuroergonomics for Flight Safety, a rare credit attributed to less than thirty researchers in the world. He is leading the Neuroergonomics and Human Factors Department, a team composed of 18 permanent and non-permanent members with an interdisciplinary expertise in Neuroscience, Signal Processing, Computer Science, and Human Factors. His research focuses on understanding the neural correlates of human error in real-life situations and the implementation of BCI and cognitive countermeasures to mitigate human error. His department receives substantial grants and his research has been published in international journals such as Neuroimage, Behavioral Brain Research, IEEE, PLOS ONE, and Human Factors. His innovative work has also led to four international patents that are currently implemented in modern civilian aircrafts.
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