Current Research in Neuroadaptive Technology

1st Edition - November 13, 2021
Editors: Stephen H. Fairclough, Thorsten O. Zander
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 2 1 4 1 3 - 8
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 2 1 4 1 4 - 5

Current Research in Neuroadaptive Technology provides readers with insight into the state-of-the-art field of neuroadaptive technology. The book covers the breadth and depth o… Read more

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Current Research in Neuroadaptive Technology provides readers with insight into the state-of-the-art field of neuroadaptive technology. The book covers the breadth and depth of current research in this field, covering a range of application domains in sufficient technical detail. The multidisciplinary character of this field means that the publication of key research is often fragmented across specialist journals. Here, the editors have consolidated current research, carefully selecting key topics that are clustered around the concept of neuroadaptive technology. In summary, the book meets the needs of readers by consolidating multidisciplinary research around a nascent technological concept.

The topic of neuroadaptive technology is novel and contemporary and editors Dr. Stephen H. Fairclough and Dr. Thorsten O. Zander have captured issues related to this emerging technology at the point of inception. It is a key reference for biomedical engineers and researchers in neural engineering, biomedical engineering, computer science, and mathematics.

Cover image
Title page
Table of Contents
Copyright
List of contributors
Preface
Chapter 1: Designing human-computer interaction with neuroadaptive technology
Abstract
Acknowledgement
1.1. Introduction
1.2. Can neuroadaptive technology improve the quality of human-computer interaction?
1.3. Design of goals for neuroadaptive technology
1.4. Neuroadaptive autonomy: striking a balance
1.5. Summary
References
Chapter 2: Defining neuroadaptive technology: the trouble with implicit human-computer interaction
Abstract
Acknowledgements
2.1. Introduction
2.2. Background
2.3. Defining human-computer interaction and neuroadaptive technology
2.4. Sample scenarios
2.5. Discussion
References
Chapter 3: The multi-stage theory of neurofeedback learning: a framework for understanding mechanisms
Abstract
Note
3.1. Introduction
3.2. Multi-stage theory
3.3. Extending the theory's reach
3.4. Concluding remarks
References
Chapter 4: Towards neuroadaptive modeling: assessing the cognitive states of pilots through passive brain-computer interfacing
Abstract
Acknowledgements
4.1. Introduction
4.2. Methods
4.3. Results
4.4. Discussion
References
Chapter 5: Tangible physiological devices for positive computing, a retrospective
Abstract
5.1. Introduction (the high-level overview)
5.2. Background: physiological objects and spaces
5.3. Forewords: our take on tangible physiological devices
5.4. Generation 1: spatial augmented reality
5.5. Generation 2: electronics
5.6. Generation 3: modularity
5.7. Discussion
5.8. Conclusion
5.9. Contributions
References
Chapter 6: The influence of a neuroadaptive game as a distraction from pain: a fNIRS study
Abstract
6.1. Pain, attention, and dynamic difficulty adjustment
6.2. Neuroadaptive gaming
6.3. Construction of a neuroadaptive game prototype
6.4. The creation of the neuroadaptive game
6.5. Evaluation of neuroadaptive technology
6.6. Testing neuroadaptive technology: an example
6.7. Summary and conclusions
References
Chapter 7: Ecological measures of cognitive impairments in aeronautics: theory and application
Abstract
Ethical statement
Acknowledgements
7.1. Introduction
7.2. Methodological considerations
7.3. Experimental data
7.4. Discussion
7.5. Conclusion
References
Chapter 8: Transcranial Direct-Current Stimulation (tDCS) attenuates perceived temporal demand during simulated laparoscopic tasks
Abstract
Acknowledgements
Note
8.1. Introduction
8.2. Methods
8.3. Results
8.4. Discussion
8.5. Conclusions
References
Chapter 9: Adaptive virtual reality
Abstract
9.1. Introduction
9.2. Adaptive VR
9.3. Application of adaptive VR
9.4. Open loop monitoring for adaptive VR: an example
9.5. Conclusions
References
Chapter 10: Possibilities and pitfalls for the co-registration of mobile EEG and eye-tracking in the study of economic decision-making in naturalistic settings
Abstract
List of abbreviations
Acknowledgements
10.1. Introduction
10.2. Value processing and the brain
10.3. Embodied decision making and the MoBI approach
10.4. Using mobile EEG and eye-tracking to examine economic decisions for products
10.5. General summary and future directions
References
Chapter 11: The impact of electrode shifts on BCI classifier accuracy
Abstract
11.0. Introduction
11.1. Theoretical background
11.2. Investigation of electrode shifts in BCI
11.3. Conclusion
References
Chapter 12: Walking improves the performance of a brain-computer interface for group decision making
Abstract
Acknowledgements
12.1. Introduction
12.2. Methods
12.3. Results
12.4. Discussions and conclusions
References
Chapter 13: Spontaneous radiofrequency emission from electron spins within Drosophila: a novel biological signal
Abstract
Contributions
Acknowledgements
13.1. Introduction
13.2. Results
13.3. Resonator experiments at 2.6 GHz
13.4. Radiofrequency emission during activation of the nervous system by temperature-sensitive cation channels
References
Abstracts from the First Neuroadaptive Technology Conference, 2017
COGNITIVE PROBING FOR AUTOMATED NEUROADAPTATION
ENDOWING THE MACHINE WITH ACTIVE INFERENCE: A GENERIC FRAMEWORK TO IMPLEMENT ADAPTIVE BCI
LEARNING FROM LABEL PROPORTIONS IN BCI: A SYMBIOTIC DESIGN FOR STIMULUS PRESENTATION AND SIGNAL DECODING
FROM UNIVARIATE TO MULTIVARIATE ANALYSIS OF fNIRS DATA
A GENERALIZED DEEP LEARNING FRAMEWORK FOR CROSS-DOMAIN LEARNING IN BRAIN COMPUTER INTERFACES
TIME-FREQUENCY SENSITIVITY CHARACTERIZATION OF SINGLE-TRIAL OSCILLATORY EEG COMPONENTS
EEG, ECG AND EOG RESPONSES TO AUTOMATED, REAL DRIVING
CLASSIFICATION OF CONCENTRATION LEVELS USING DEEP NEURAL NETWORKS
ASSESSING IMPLICIT ATTITUDES DURING HUMAN-TECHNOLOGY INTERACTION BASED ON NEUROELECTRICAL EVIDENCE
BETWEEN-SUBJECT TRANSFER LEARNING FOR CLASSIFICATION OF ERROR-RELATED SIGNALS IN HIGH-DENSITY EEG
TRACING RHYTHMIC REGULARITY PROCESSING: BEAT-BASED BETA POWER MODULATION IN EEG SOURCE SPACE
EXPRESS ESTIMATION OF BRAIN RHYTHM POWER FOR LOW-LATENCY NEUROFEEDBACK
INVESTIGATING NEUROADAPTIVE TECHNOLOGY FOR SPEED READING APPLICATIONS
TOWARD NEUROADAPTIVE PERSONAL LEARNING ENVIRONMENTS
GAZE DIRECTION AND THE EEG MARKER FOR INTENTION/EXPECTATION IN HYBRID INTERFACES
WEARABLE SENSORS, DRIVING AND THE VISUALIZATION OF CARDIOVASCULAR STRESS DURING EVERYDAY LIFE
EVALUATING FNIRS-BASED WORKLOAD DISCRIMINATION IN A REALISTIC DRIVING SCENARIO
FIVE LAYER MODEL FOR PHYSIOLOGICAL COMPUTING
DETECTION OF FEEDBACK-RELATED MENTAL STATES WITH ERROR-RELATED SPECTRAL PERTURBATION
A COLLABORATIVE BCI TRAINED TO AID GROUP DECISIONS IN A VISUAL SEARCH TASK WORKS WELL WITH SIMILAR TASKS
PASSIVE BCI TOOLS FOR MENTAL STATE ESTIMATION IN AEROSPACE APPLICATIONS
CORTICO-CORTICAL SPECTRAL RESPONSES ELICITED BY CLOSED LOOP STIMULATION IN THE SHEEP SOMATOSENSORY CORTEX
CLASSIFICATION OF EMOTIONS USING CONVOLUTIONAL NEURAL NETWORKS – AN EEG STUDY
CLASSIFICATION OF CORTICAL RESPONSES TO VISUAL TARGETS DURING A PHYSICAL-COGNITIVE INTERACTION TASK
INVESTIGATING RESPONSES TO LETTER PRESENTATIONS IN A SEGMENT SPELLER
USING BCIS FOR BENCHMARKING ADAPTIVE AND LOW-RESOLUTION DAQ EEG APPROACHES
INTELLIGENT THRESHOLD SELECTION FOR BIOCYBERNETIC LOOP IN AN ADAPTIVE VIDEO GAME CONTEXT
MOBILE BRAIN / BODY IMAGING (MoBI) OF PHYSICAL INTERACTION WITH DYNAMICALLY MOVING OBJECTS
EEG AND EMG SYNCHRONIZATION AND JITTER ESTIMATION FOR MOBI EXPERIMENTS
NEURAL CORRELATES OF HUMAN SINGLE- AND DUAL-TASK NATURAL WALKING IN THE URBAN ENVIRONMENT
NEUROETHICS FOR NEUROADAPTIVE TECHNOLOGY: THE CASE OF PASSIVE BRAIN-COMPUTER INTERFACES
HACKING MINDS, HACKING BRAINS, HACKING AUGMENTED BODIES: ETHICAL ASPECTS OF NEUROHACKING
EVALUATING BRAIN READING'S PRACTICAL APPLICABILITY
INTERACTING WITH WEARABLE COMPUTERS BY MEANS OF FUNCTIONAL ELECTRICAL MUSCLE STIMULATION
MEASURING ACADEMIC STRESS ‘IN THE WILD’ WITH WEARABLE SENSORS: REMOVAL OF NOISE FROM WEARABLE SENSOR DATA USING FIR FILTERS
MOBILE BRAIN/BODY IMAGING (MOBI) OF SPATIAL KNOWLEDGE ACQUISITION DURING UNCONSTRAINED EXPLORATION IN VR
SIGNAL ANALYSIS OF MOTOR IMAGERY TASKS FOR SELF-PACED BCI APPLICATIONS
FUNCTIONAL CORTICAL NETWORKS FOR AUDITORY DISTRACTOR SUPRESSION DURING A REALISTIC VISUAL SEARCH TASK
RE-THINKING BCI MODELS AS NOISY SENSORS FOR NEURAL ANALYSIS
A BIOFEEDBACK APPROACH TO INVESTIGATE NEUROCOGNITIVE MECHANISMS OF FEEDBACK-BASED LEARNING
FINDING EEG FREQUENCY BANDS RELATED TO CONCENTRATION
DEVELOPMENT OF A NEUROADAPTIVE GAMING TECHNOLOGY TO DISTRACT FROM PAINFUL PROCEDURES
CORTICAL SOURCE LOCALIZATION OF EEG BIOMARKERS IN A COGNITIVE BRAIN-COMPUTER INTERFACE MONITORING WORKING MEMORY LOAD
DESIGNING AND UNDERSTANDING CONVOLUTIONAL NETWORKS FOR DECODING EXECUTED MOVEMENTS FROM EEG
SIGMABOX: TOWARDS A SIMPLE AND EFFICIENT MATLAB TOOLBOX FOR EEG SIGNAL PROCESSING AND CLASSIFICATION
EEG-BASED BIOMETRIC AUTHENTICATION: A PRELIMINARY STUDY
MEASURING COGNITIVE CONFLICT IN VIRTUAL REALITY
NEUROPHYSIOLOGICAL CORRELATES OF EFFICIENT LEARNING IN THE NEUROFEEDBACK PARADIGM
USER IDENTIFICATION FROM FNIRS DATA USING DEEP LEARNING
ENHANCING BCI PERFORMANCE THROUGH COLLABORATION OF EYE GAZE AND SSVEP
LABELLING OF MOVEMENT ONSETS BASED ON EXOSKELETON JOINT DATA
INVESTIGATING METRICS FOR MEASURING AND REMINDING MINDFULNESS OF SCHOOL STUDENTS
Abstracts from the Second Neuroadaptive Technology Conference, 2019
TOWARDS AN ETHICAL DEFINITORY FRAMEWORK FOR BOTH TRADITIONAL AND NOVEL HUMAN-COMPUTER INTERACTION PARADIGMS
A NEUROADAPTIVE APPROACH TO ANALGESIC GAMING
INVESTIGATING THE INFLUENCE OF RSVP DISPLAY PARAMETERS ON WORKING MEMORY LOAD USING ELECTROENCEPHALOGRAPHY
TOWARDS BUILDING NEUROADAPTIVE READING APPLICATIONS: ASSESSING DIFFERENCES IN MENTAL WORKLOAD INDUCED BY TEXT READABILITY LEVELS AND PRESENTATION SPEEDS ON SINGLE-SUBJECT LEVEL
CAAD MODELING WITH VISUAL-ERP BCI
MAY ALPHA NEUROFEEDBACK AFFECT MOTOR IMAGERY BCI PERFORMANCE?
DIFFERENTIAL EFFECTS OF NEUROFEEDBACK LATENCY ON THE INCIDENCE RATE, AMPLITUDE AND DURATION OF ALPHA-BURSTS
MULTI-STAGE THEORY OF NEUROFEEDBACK LEARNING
MODULAR BIOFEEDBACK: BUILD YOUR OWN TANGIBLE EXPERIENCE
MODELING BIOCYBERNETIC ADAPTATION THROUGH FEEDBACK CONTROL SYSTEMS PRINCIPLES: IMPLICATIONS IN HUMAN-COMPUTER INTERACTION AND VIRTUAL REALITY APPLICATIONS
ON THE USE OF PHYSIOLOGICAL MEASURES TO MONITOR OPERATOR DYADS
THE AUTOMATIC CLASSIFICATION OF HUMAN FACTORS ASSOCIATED WITH DECISIONS INVOLVING RISK DURING DRIVING SIMULATION
TOWARDS NEUROADAPTIVE TECHNOLOGY USING TIME WARPED DISTANCES FOR SIMILARITY EXPLORATION OF BRAIN DATA
ATTENTIONAL CONTROL DURING THE FLOW EXPERIENCE IN VIRTUAL REALITY GAMES
EXAMINING ECONOMIC DECISIONS FOR HOUSEHOLD PRODUCTS USING MOBILE EEG
WALKING IMPROVES THE PERFORMANCE OF A BRAIN-COMPUTER INTERFACE FOR GROUP DECISION MAKING
FEMG AND EMOTION IN VIRTUAL REALITY
PROMOTING DIGITAL WELLBEING THROUGH REAL-TIME STATE CLASSIFICATION OF PSYCHOPHYSIOLOGICAL SENSOR NETWORKS
GROUP EYE TRACKING RESEARCH AND APPLICATIONS
APPLICATION OF DEEP LEARNING IN LIP READING
SPONTANEOUS RADIOFREQUENCY EMISSION FROM NONEQUILIBRIUM ELECTRON SPINS WITHIN DROSOPHILA
SINGLE SESSION TRANSCRANIAL DIRECT CURRENT STIMULATION (TDCS) CAN IMPROVE ROBOTIC SUTURING SKILLS IN SURGICAL TRAINEES
APPREHENDING AUDITORY ACTIVITY IN ECOLOGICAL CONTEXTS WITH UNOBTRUSIVE EEG
THE IMPACT OF ELECTRODE SHIFTS ON BCI CLASSIFIER ACCURACY
N170 COMPONENTS OF REAL AND COMPUTER-GENERATED FACIAL IMAGES
USING LINEAR DECONVOLUTION TO ACCOUNT FOR OVERLAPPING BRAIN POTENTIALS: AN EYE-FIXATION RELATED POTENTIALS STUDY
ISOLATING AFFECTIVE INFLUENCES ON IMPLICIT CURSOR CONTROL
Index

Stephen H. Fairclough

Stephen Fairclough obtained his undergraduate degree in Psychology from University of Central Lancashire in 1985. He received his PhD from Loughborough University in 2000 where he worked as a Research Fellow at Human Sciences and Advanced Technology (HUSAT) Research Centre. He currently is a Professor of Psychophysiology in the School of Psychology at Liverpool John Moores University (LJMU). He has been involved in applied psychophysiological and neuroscientific research for over twenty-five years. His main areas of methodological expertise cover EEG, fNIRS and cardiovascular in both laboratory and field settings. He is a director on the Executive of the Human Factors and Ergonomics Society (European Chapter) and a member of the editorial board for IEEETransactions of Affective Computing. He has co-edited two collections on physiological computing research and four journal special issues. He is currently one of the General Chairs for the Neuroadaptive Technology Conference and co-founder and co-leaderof the Society for Neuroadaptive Technology.

Affiliations and expertise

School of Psychology, Liverpool John Moores University (LJMU), UK

Thorsten O. Zander

Dr. Thorsten Zander took a degree in Mathematics at the Westfalische Wilhelms-Universitat, Munster, Germany, and his doctorate at the Institute of Human-Machine-Systems at Technical University Berlin, before embarking on a distinguished career at various research institutions, including Affiliated Research Scientist at the Institute for Knowledge at Technical University Graz, Austria, Project Leader at Max-Planck-Institute for Intelligent Systems, and ongoing habilitation process in the Department of Psychology and Ergonomics at Technical University Berlin. Dr. Zander is currently Chair for Neuroadaptive Human-Computer Interaction, Brandenburg Technical University, Germany. Dr. Zander is also an International Affiliate of the Learning, Educational Achievement, and Life Course Development (LEAD) excellence graduate school at the University of Tuebingen, Germany. Dr. Zander has been active in development and partnership with industry, including foundation and leadership of Zander Laboratories B.V., Scientific Advisor at Eagle Science B.V., Scientific Advisor at Brain Vision LLC, and Scientific Advisor at Brain Products. In addition, Dr. Zander also has many scientific achievements, including definition and validation of Passive Brain-Computer-Interfaces, foundation and leadership of the Community for Passive BCI Research, foundation and leadership of the Team PhyPA working group at Technical University Berlin, and co-foundation of Implicit Human-Technology Interaction

Affiliations and expertise

Chair for Neuroadaptive Human-Computer Interaction, Brandenburg University of Technology, Germany

Life Sciences

Physical Sciences & Engineering

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