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
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Techn.
ISBN-13
978-0-12-811927-3 (9780128119273)
Schweitzer Klassifikation
Introduction1. Progress and Direction in Neuroergonomics
Methods2. Electroencephelography for Neuroergonomics3. 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 Neuroergonomics6. Brain Computer Interfaces for Neuroergonomics7. Transcranial Doppler Sonography for Neuroergonomics8. Simulators and Behavioral Research Methods for Neuroergonomics9. Neuroergonomics for Aviation10. MoBI - Mobile Brain Body Imaging11. Experiments with participants: Some ethical considerations
Neuroadaptive Interfaces and Operator Assessment12. Measuring the Redline for Mental Overload Using EEG and fNIRS: A Role for Neural Efficiency?13. Drowsiness Detection during Driving Task Using fNIRS14. Neuroergonomic Multimodal Neuroimaging During a Simulated Aviation Pursuit Task15. Is Mindfulness Helping the Brain to Drive?16. Tracking Team Mental Workload by Multimodal Measurements in The Operating Room17. Towards Brain-Based Interaction Between Humans and Technology: Does Age Matter?18. Curvilinear Basis for Cognitive Load State Classification19. Computational Models for Near Real-Time Performance Predictions Based on Physiological Measures of Workload20. Mental Workload Assessment as Taxonomic Tool for Neuroergonomics21. Preliminary Validation of an Adaptive Tactical Training Model: Cognitive Alignment with Performance Targeted Training Intervention Model
Neurostimulation Applications22. Concurrent fNIRS and TMS for Neurocognitive Enhancement on a Speed of Processing Task23. Neuromodulatory Effects of Transcranial Direct Current Stimulation Revealed by Functional Magnetic Resonance Imaging24. Neurophysiological Correlates of tDCS-induced Modulation of Cortical Sensorimotor Networks: A Simultaneous fNIRS-EEG study25. The use of Online/Offline Terminology for Transcranial Direct Current
Emerging Applications in Decision-making, Usability, Trust and Emotions26. Neural Signatures of Advice Utilization During Human-Machine Agent Interactions: Functional Magnetic Resonance Imaging and Effective Connectivity Evidence27. Psychophysical Equivalence of Static Versus Dynamic Stimuli in a Two Alternative Forced Choice Detection Task28. Functional Near Infrared Spectroscopy: Proof of Concept for its Application in Social Neuroscience29. Quantifying Brain Hemodynamics during Neuromuscular Fatigue30. The Assessment of Emotions and Decision Making in Everyday Living Using fNIRS31. Web Usability Testing with Concurrent fNIRS and Eye Tracking32. 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
