| A Generic Personal Assistant Agent Model for Support in Demanding Tasks | | BIBA | Full-Text | 3-12 | |
| Tibor Bosse; Rob Duell; Mark Hoogendoorn; Michel C. A. Klein; Rianne van Lambalgen; Andy van der Mee; Rogier Oorburg; Alexei Sharpanskykh; Jan Treur; Michael de Vos | |||
| Human task performance may vary depending on the characteristics of the human, the task and the environment over time. To ensure high effectiveness and efficiency of the execution of tasks, automated personal assistance may be provided to task performers. A personal assistant agent may constantly monitor the human's state and task execution, analyse the state of the human and task, and intervene when a problem is detected. This paper proposes a generic design for a Personal Assistant agent model which can be deployed in a variety of domains. Application of the Personal Assistant model is illustrated by a case study from the naval domain. | |||
| Adaptive Interfaces in Driving | | BIBAK | Full-Text | 13-19 | |
| Rino F. T. Brouwer; Marieka Hoedemaeker; Mark A. Neerincx | |||
| The automotive domain is an excellent domain for investigating augmented
cognition methods, and one of the domains that can provide the applications. We
developed, applied and tested indirect (or derived) measures to estimate driver
state risks, validated by direct state-sensing methods, with major European
vehicle manufacturers, suppliers and research institutes in the project AIDE
(Adaptive Integrated Driver-vehicle InterfacE). The project developed an
interface with the driver that integrates different advanced driver assistant
systems and in-vehicle information systems and adapted the interface to
different driver or traffic conditions. This paper presents an overview of the
AIDE project and will then focus on the adaptation aspect of AIDE. Information
presented to the driver could be adapted on basis of environmental conditions
(weather and traffic), and on basis of assessed workload, distraction, and
physical condition of the driver. The adaptation of how information is
presented to the driver or the timing of when information is presented to the
driver is of importance. Adapting information, however, also results in systems
that are less transparent to the driver. Keywords: In-car services; workload; adaptive user interface; central management | |||
| Using Context to Identify Difficult Driving Situations in Unstructured Environments | | BIBA | Full-Text | 20-29 | |
| Kevin R. Dixon; Justin D. Basilico; J. Chris Forsythe; Wilhelm E. Kincses | |||
| We present a context-based machine-learning approach for identifying difficult driving situations using sensor data that is readily available in commercial vehicles. The goal of this system is improve vehicle safety by alerting drivers to potentially dangerous situations. The context-based approach is a two-step learning process by first performing unsupervised learning to discover meaningful regularities, or "contexts," in the vehicle data and then performing supervised learning, mapping the current context to a measure of driving difficulty. To validate the benefit of this approach, we collected driving data from a set of experiments involving both on-road and off-road driving tasks in unstructured environments. We demonstrate that context recognition greatly improves the performance of identifying difficult driving situations and show that the driving-difficulty system achieves a human level of performance on cross-validation data. | |||
| Neurally-Driven Adaptive Decision Aids | | BIBAK | Full-Text | 30-34 | |
| Alexandra Geyer; Jared Freeman; Denise M. Nicholson; Cali M. Fidopiastis; Phan Luu; Joseph Cohn | |||
| Warfighters are constantly challenged with increasingly complex mission
environments, roles, and tasks, which require rapid and accurate decision
making. Most current military and commercial decision aids leverage a single
strategy: they retrieve and fuse information about well-defined objects and
events for the user. Such aids effectively discourage users from considering
contextual information and patterns that may help them recognize or think
critically about hostile or innocent events. If a decision aiding system were
to be truly effective, its adaptive strategies should be driven by more than
manipulation of well-defined information presented to the user. In this paper,
we propose several critical factors -- (1) Information state, (2) User
cognitive state, and (3) Interaction state -- that will enable for discern what
must be decided and by when; discriminate which cognitive state and process are
in play; and assess interactions (queries, selections, etc.) with the
information. Most importantly, these factors will allow for a decision aid to
capitalize on -- the distinctly human ability to find meaning in swarm of
objects and events being perceived. Keywords: adoptive decision aids; intuition; cognitive state; warfighters | |||
| Understanding Brain, Cognition, and Behavior in Complex Dynamic Environments | | BIBAK | Full-Text | 35-41 | |
| Scott E. Kerick; Kaleb McDowell | |||
| Many challenges remain for understanding how the human brain functions in
complex dynamic environments. For example, how do we measure brain physiology
of humans interacting in their natural environments where data acquisition
systems are intrusive and environmental and biological artifacts severely
confound brain source signals? How do we understand the full context within
which the human brain is operating? How do we know which information is most
meaningful to extract from the data? How can we best utilize that extracted
information and what are the implications for human performance? The papers
comprising this section address these questions from conceptual, technical, and
applied perspectives. It is clearly seen that significant progress has been
made since the inception of the Augmented Cognition program and that, to
overcome these challenges, a continued multidisciplinary approach is required
across basic and applied research from cognitive scientists, neuroscientists,
computer scientists, and engineers. Keywords: electroencephalography (EEG); natural environment; operational neuroscience;
Augmented Cognition; cognitive engineering; human dimension | |||
| Designing a Control and Visualization System for Off-Highway Machinery According to the Adaptive Automation Paradigm | | BIBAK | Full-Text | 42-50 | |
| Stefano Marzani; Francesco Tesauri; Luca Minin; Roberto Montanari; Caterina Calefato | |||
| This paper aims at describing the requirements of an off-highway
human-machine system able to recognize potential risky situations and
consequently prevent them. The developed methodology is based on two techniques
derived from the field of human factors studies, namely the Hierarchical Task
Analysis (HTA) and the Function Allocation (FA), which have been integrated and
revised to suit the specific domain of off-highway machinery. The paradigms of
adaptive automation and persuasive technology will be followed in the design
process. After the off-highway domain analysis a system aiming at improving
operator and machine safety is presented. The information system extends the
human intelligence monitoring the stability of the machine. Keywords: Adaptive Automation; Collision; Function Allocation; Human-Machine
Interaction; Hierarchical Task Analysis; Off-Highway Vehicles; Overun;
Rollover; Runover; Safety; Tractors | |||
| Context-Dependent Force-Feedback Steering Wheel to Enhance Drivers' On-Road Performances | | BIBAK | Full-Text | 51-57 | |
| Luca Minin; Stefano Marzani; Francesco Tesauri; Roberto Montanari; Caterina Calefato | |||
| In this paper the topic of the augmented cognition applied to the driving
task, and specifically to the steering maneuver, is discussed. We analyze how
the presence of haptic feedback on the steering wheel could help drivers to
perform a visually-guided task by providing relevant information like vehicle
speed and trajectory. Starting from these considerations, a Context-Dependant
Steering Wheel force feedback (CDSW) had been developed, able to provide to the
driver the most suitable feeling of the vehicle dynamics according to the
driven context. With a driving simulator the CSWD software had been tested
twice and then compared with a traditional steering wheel. Keywords: adaptive steering wheel; augmented cognition; driver performance; force
feedback; haptic feedback; lane change | |||
| Where Is My Stuff? Augmenting Finding and Re-finding Information by Spatial Locations and Icon Luminance | | BIBAK | Full-Text | 58-67 | |
| J. Michelle Moon; Wai-Tat Fu | |||
| We studied how spatial locations and luminance affect finding and re-finding
information in a desktop environment. In an experiment conducted with computer
icons, fixed locations led to more frequent accesses to icons while change of
luminance led to worse recall of icon titles and locations. In an analysis of
icon access transition, a sequential search pattern was identified in earlier
sessions, which suggests that participants were minimizing efforts in external
search and were not utilizing internal memory of titles and locations yet. In
later sessions, icon accesses were more focused to information directly
relevant to search tasks as participants started using titles and locations for
re-finding icons. Results are consistent with the notion that information
search behavior is adaptive to the cost-benefit structure of the interface, and
search strategies are adaptive to different external representations of icons.
Results also suggest that both external representations and human information
processes are critical in determining the effectiveness of different GUI
designs. Keywords: Adaptive human behavior; re-finding information; spatial memory; interface
design | |||
| Adaptive Work-Centered and Human-Aware Support Agents for Augmented Cognition in Tactical Environments | | BIBA | Full-Text | 68-77 | |
| Martijn Neef; Peter-Paul van Maanen; Peter Petiet; Maartje Spoelstra | |||
| We introduce a support system concept that offers both work-centered and human-aware support for operators in tactical command and control environments. The support system augments the cognitive capabilities of the operator by offering instant, personalized task and work support. The operator obtains support by entering into a collaborative agreement with support agents. Such an agreement creates opportunities to establish adaptive capabilities and human-aware support features. We describe the concept in and propose an experimental design to evaluate its effectiveness in tactical environments. | |||
| Designing Cognition-Centric Smart Room Predicting Inhabitant Activities | | BIBAK | Full-Text | 78-87 | |
| Andrey Ronzhin; Alexey Karpov; Irina S. Kipyatkova | |||
| Assignment of easy-to-use and well-timed services staying invisible for a
user is one of important features of ambient intelligent. Multimodal user
interface capable to perceive speech, movements, poses and gestures of
participants in order to determinate their needs provides the natural and
intuitively understandable way of interaction with the developed intelligent
meeting room. Awareness of the room about spatial position of the participants,
their current activities, roles in a current event, their preferences helps to
predict more accurately the intentions and needs of participants. Technological
framework, equipment and description of technologies applied to the intelligent
meeting room are presented. Some scenarios and data structures used for a
formalization of context and behavior information from practical human-human,
human-machine and machine-machine interaction are discussed. Keywords: ambient intelligence; cognitive-centric design; multimodal interfaces;
context awareness; smart home; intelligent meeting room | |||
| Context-Aware Team Task Allocation to Support Mobile Police Surveillance | | BIBAK | Full-Text | 88-97 | |
| Jan Willem Streefkerk; Myra P. van Esch-Bussemakers; Mark A. Neerincx | |||
| To optimally distribute tasks within police teams during mobile
surveillance, a context-aware task allocation system is designed and evaluated
with end-users. This system selects and notifies appropriate team members of
current incidents, based on context information (officer availability, officer
proximity to the incident and incident priority) and decision rules. Eight
teams of three experienced police officers evaluated this system in a
surveillance task through a virtual environment, comparing it to a non-adaptive
system. Task performance, communication, workload and preferences were
measured. Results show that team communication, decision making and response
times improve using the adaptive system and that this system is preferred. We
conclude that context-aware task allocation helps police teams to coordinate
incidents efficiently. Keywords: Context-aware computing; mobile computing; police surveillance; task
allocation; notification | |||
| Operational Brain Dynamics: Data Fusion Technology for Neurophysiological, Behavioral, and Scenario Context Information in Operational Environments | | BIBAK | Full-Text | 98-104 | |
| Don M. Tucker; Phan Luu | |||
| Classical laboratory studies of human performance have always required some
form of data integration, such as the synchronization of stimulus display,
behavioral accuracy, and reaction time. Studies of performance in operational
environments have typically been limited in the precision of behavioral
observations. As improved digital informatics have expanded the laboratory data
acquisition from a few bytes to terabytes, there has been a similar expansion
in both the opportunities and the challenges for data fusion. Keywords: EEG; information systems; brain activity; neuroergonomics | |||
| Characterizing Cognitive Adaptability via Robust Automated Knowledge Capture | | BIBA | Full-Text | 107-113 | |
| Robert G. Abbott; Chris Forsythe | |||
| Applications such as individually tailored training and behavior emulation call for cognitive models tailored to unique individuals on the basis of empirical data. While the study of individual differences has been a mainstay of psychology, a prevailing assumption in cognitive theory and related modeling has been that cognitive processes are largely invariant across individuals and across different conditions for an individual. Attention has focused on identifying a universally correct set of components and their interactions. At the same time, it is known that aptitudes for specific skills vary across individuals and different individuals will employ different strategies to perform the same task [3]. Moreover, individuals will perform tasks differently over time and under different conditions (e.g. Taylor et al, 2004). To reach their full potential, systems designed to augment cognitive performance must thus account for such between- and within-individual differences in cognitive processes. We propose that cognitive adaptability is a trait necessary to explain the inherently dynamic nature of cognitive processes as individuals adapt their available resources to ongoing circumstances. This does not imply a "blank slate;" humans are predisposed to process information in particular ways. Instead, we assert that given variation in the structure and functioning of the brain, there exists inherent flexibility that may be quantified and used to predict differences in cognitive performance between individuals and for a given individual over time. This paper presents an early report on research we are undertaking to discover the dynamics of cognitive adaptability, with emphasis on a task environment designed to evoke and quantify adaptation in controlled experiments. | |||
| Implications of User Anxiety in the Evaluation of Deception in Web Sites | | BIBAK | Full-Text | 114-119 | |
| Brent Auernheimer; Marie Iding; Martha E. Crosby | |||
| In a pilot study, we investigated the effect of anxiety on users'
susceptibility to deceptive information on Web pages. Specifically, we
manipulated the perceived control and associated anxiety of participants with
and without visual disabilities as they used an assistive technology, a screen
reader. Preliminary findings indicated that anxious participants (i.e., without
visual disabilities) using the unfamiliar assistive technology were more
susceptible to deception and expressed more suspicion regarding the Web pages.
We interpret these preliminary findings as consistent with the work of Whitson
and Galinsky [1] and discuss implications for further research in Web site
credibility determinations and users' susceptibility to deception. Keywords: Deception; Web Sites; Anxiety; Control; Assistive Technology | |||
| Investigation of Sleepiness Induced by Insomnia Medication Treatment and Sleep Deprivation | | BIBAK | Full-Text | 120-127 | |
| Ioanna Chouvarda; Emmanouil Michail; Athina Kokonozi; Luc Staner; Nathalie Domis; Nicos Maglaveras | |||
| The main objective of this work is the study of EEG signals in order to
investigate sleepiness induced from drug administration for insomnia and sleep
deprivation. Data used in this work were obtained from real experiments in
FORENAP, France and in CERTH, Thessaloniki, Greece. The features under
consideration are Power Spectrum in certain frequency areas, alpha slow-wave
index (ASI) and Fractal Dimension (FD) for placebo and verum subjects. Studying
these features in the above groups, we found that sleepiness due to hypnotic
medication and due to sleep deprivation can cause different behaviour in brain
activity at certain locations. These EEG characteristics could be used for the
classification of the medication intake (verum or placebo) and its effect. Keywords: insomnia; sleep deprivation; EEG signals | |||
| Activity Awareness and Social Sensemaking 2.0: Design of a Task Force Workspace | | BIBAK | Full-Text | 128-137 | |
| Gregorio Convertino; Lichan Hong; Les Nelson; Peter Pirolli; Ed H. Chi | |||
| Task forces of expert knowledge workers would benefit from more advanced web
tools supporting activity awareness and social sensemaking. This paper proposes
the design of a task force workspace, which is under development. It introduces
the problem through a scenario, specifies requirements, illustrates a modeling
approach and the mockups of the functions in the proposed workspace. Design
issues and future work are finally discussed. Keywords: Awareness; Sensemaking; Task Force; Roles; User Modeling; CSCW Design; RSS
or Atom Feeds | |||
| Use of Deception to Improve Client Honeypot Detection of Drive-by-Download Attacks | | BIBAK | Full-Text | 138-147 | |
| Barbara Endicott-Popovsky; Julia Narvaez; Christian Seifert; Deborah A. Frincke; Lori Ross O'Neil; Chiraag Uday Aval | |||
| This paper presents the application of deception theory to improve the
success of client honeypots at detecting malicious web page attacks from
infected servers programmed by online criminals to launch drive-by-download
attacks. The design of honeypots faces three main challenges: deception, how to
design honeypots that seem real systems; counter-deception, techniques used to
identify honeypots and hence defeating their deceiving nature; and counter
counter-deception, how to design honeypots that deceive attackers. The authors
propose the application of a deception model known as the deception planning
loop to identify the current status on honeypot research, development and
deployment. The analysis leads to a proposal to formulate a landscape of the
honeypot research and planning of steps ahead. Keywords: deception; counter-deception; honeypots; drive-by-downloads; cyber-attacks | |||
| Capturing and Building Expertise in Virtual Worlds | | BIBAK | Full-Text | 148-154 | |
| Jared Freeman; Webb Stacy; Jean MacMillan; Georgiy Levchuk | |||
| Model-driven simulation can make the design and delivery of instruction more
efficient and effective. We describe two computational models that support both
the design and delivery of instruction. BEST (the Benchmarked Experiential
System for Training) can guide experts through the space of domain problems
during the knowledge engineering phase of instructional design; it can guide
trainees through the space of training objectives during instruction. PRESTO
(Pedagogically Relevant Engineering of Scenarios for Training Objectives)
builds scenarios on the fly to elicit the knowledge of experts during
instructional design, and to satisfy the instructional objectives of trainees. Keywords: Adaptive instruction; knowledge engineering; Constraint Logic Programming;
Markov Decision Process | |||
| Conformity out of Diversity: Dynamics of Information Needs and Social Influence of Tags in Exploratory Information Search | | BIBAK | Full-Text | 155-164 | |
| Ruogu Kang; Thomas George Kannampallil; Jibo He; Wai-Tat Fu | |||
| We studied the dynamic effects of information needs and social influence of
tags in an exploratory search task. Although initially differences in
information needs led to diversity in tag choices, this diversity disappeared
as participants collaboratively tagged the same set of resources. Our findings
are in general consistent with the notion that people conform to the collective
interpretation of contents in an information system. In addition, our results
showed that conformity does not only arise out of imitation of behavior, but
also from the same underlying semantic interpretation or knowledge structures
of users as they engage in informal collaboration through the social tagging
system. Implications for design of social information system are discussed. Keywords: Exploratory search; tag choice; information needs diversity; semantic
interpretation of tags | |||
| Trail Patterns in Social Tagging Systems: Role of Tags as Digital Pheromones | | BIBAK | Full-Text | 165-174 | |
| Thomas George Kannampallil; Wai-Tat Fu | |||
| The popularity of social information systems has been driven by their
ability to help users manage, organize and share online resources. Though the
research exploring the use of tags is relatively new, two things are widely
acknowledged in the research community: (a) tags act as a medium for social
collaboration, navigation and browsing and (b) an overall stable equilibrium
exists among tag patterns due to the social nature of the tagging process. But
there is very little agreement on what causes these stable patterns. In this
paper, we take an evolutionary perspective to understand the process of tagging
to investigate whether tags act as "way finders" or digital pheromones in
social tagging systems. We investigate the existence of tag trails based on a
semantic similarity measure among existing tags. We found that over 50% of the
resources we evaluated exhibited strong trail patterns. The implications of
these patterns for the design and management of social tagging systems is
discussed. Keywords: Social Tagging Systems (STS); Stigmergy; Pheromones; Web 2.0 | |||
| Real-Time Emotional State Estimator for Adaptive Virtual Reality Stimulation | | BIBAK | Full-Text | 175-184 | |
| Davor Kukolja; Sinisa Popovic; Branimir Dropuljic; Marko Horvat; Kresimir Cosic | |||
| The paper presents design and evaluation of emotional state estimator based
on artificial neural networks for physiology-driven adaptive virtual reality
(VR) stimulation. Real-time emotional state estimation from physiological
signals enables adapting the stimulations to the emotional response of each
individual. Estimation is first evaluated on artificial subjects, which are
convenient during software development and testing of physiology-driven
adaptive VR stimulation. Artificial subjects are implemented in the form of
parameterized skin conductance and heart rate generators that respond to
emotional inputs. Emotional inputs are a temporal sequence of valence/arousal
annotations, which quantitatively express emotion along unpleasant-pleasant and
calm-aroused axes. Preliminary evaluation of emotional state estimation is also
performed with a limited set of humans. Human physiological signals are
acquired during simultaneous presentation of static pictures and sounds from
valence/arousal-annotated International Affective Picture System and
International Affective Digitized Sounds databases. Keywords: Real-Time Emotional State Estimator; Adaptive Virtual Reality Stimulation;
Artificial Neural Network; Stimuli Generation; Physiological Measurements | |||
| User's Motion for Shape Perception Using CyARM | | BIBAK | Full-Text | 185-191 | |
| Ryo Mizuno; Kiyohide Ito; Tetsuo Ono; Junichi Akita; Takanori Komatsu; Makoto Okamoto | |||
| We have developed a new sensing device, named by "CyARM". CyARM is one of
Active Perception device, based on activeness of human perception. In order to
clarify information for shape perception using CyARM, an experiment had
conducted. Results of this experiment show that shapes with sharp edges are
identified easily, but shapes with smooth edges are identified with greater
difficulty. In other words, the subjects perceived changes in distance from the
sensor to the object as object edges. Furthermore, from the results of
multi-dimensional scaling, it is suggested that object shapes perceived by the
subjects were classified according to the sharpness of the edge and by the
ratio of height and width. In addition, motion analyses were conducted. The
result shows, it is suggested that user tend to swing arm to front arm mainly
in motion of lateral direction. Keywords: Active Perception Device; CyARM; Shape Perception | |||
| Human Control Modeling Based on Multimodal Sensory Feedback Information | | BIBAK | Full-Text | 192-201 | |
| Edwardo Murakami; Toshihiro Matsui | |||
| In order to simulate the human control behavior during a manipulation task
in a remote controlled or in a X-by-wire systems, first it is necessary to
measure and analyze the human control characteristics. The aim of this research
is to measure the operator reaction time and analyze the human visual and force
sensory feedback integration related to a manipulation task. Using the
developed master-slave type experimental device it was possible to identify and
build a human operator control model related to different sensory feedback. The
human model related to visual feedback solely and visual/force feedback was
identified using the techniques of system identification methods. Keywords: Human-Machine Interface; System Identification; Reaction Time; Sensory
Feedback Information | |||
| Potential and Challenges of Body Area Networks for Affective Human Computer Interaction | | BIBAK | Full-Text | 202-211 | |
| Julien Penders; Bernard Grundlehner; Ruud J. M. Vullers; Bert Gyselinckx | |||
| The Human++ program aims at achieving highly miniaturized, wireless,
intelligent and autonomous body sensor nodes to assist our health, comfort and
lifestyle. In this paper the concept of body area network is applied to
wireless monitoring of emotions, thus opening a new, affective, dimension in
human computer interaction. A prototype body area network targeting the
monitoring of physiological responses from the autonomous system is introduced,
and tested for the classification of discrete emotions. Using data fusion and
regression analysis, we show that the wireless physiological data can be mapped
in real-time to an estimation of an individual's arousal level. Results in a
controlled environment are presented, and specific challenges that need to be
overcome for a widespread use of the technology are discussed. Finally, we show
how advances in micro-power generation devices may lead to fully autonomous
systems in the future. Keywords: Ambulatory; Body area networks; Emotion monitoring; Ultra-low-power;
Wireless | |||
| Experimental Assessment of Accuracy of Automated Knowledge Capture | | BIBAK | Full-Text | 212-216 | |
| Susan M. Stevens; Chris Forsythe; Robert G. Abbott; Charles J. Gieseler | |||
| The U.S. armed services are widely adopting simulation-based training,
largely to reduce costs associated with live training. However simulation-based
training still requires a high instructor-to-student ratio which is expensive.
Intelligent tutoring systems target this need, but they are often associated
with high costs for knowledge engineering and implementation. To reduce these
costs, we are investigating the use of machine learning to produce models of
expert behavior for automated student assessment. A key concern about the
expert modeling approach is whether it can provide accurate assessments on
complex tasks of real-world interest. This study evaluates of the accuracy of
model-based assessments on a complex task. We trained employees at Sandia
National Laboratories on a Navy simulator and then compared their simulation
performance to the performance of experts using both automated and manual
assessment. Results show that automated assessments were comparable to the
manual assessments on three metrics. Keywords: Automated assessment; Naval training systems; simulation-based training;
intelligent tutoring systems | |||
| Eye Movement as Indicators of Mental Workload to Trigger Adaptive Automation | | BIBAK | Full-Text | 219-228 | |
| Tjerk de Greef; Harmen Lafeber; Herre van Oostendorp; Jasper Lindenberg | |||
| This research describes an approach to objective assessment of mental
workload, by analyzing differences in pupil diameter and several aspects of eye
movement (fixation time, saccade distance, and saccade speed) under different
levels of mental workload. In an experiment, these aspects were measured by an
eye-tracking device to examine whether these are indeed indicators for mental
workload. Pupil diameter and fixation time both show a general significant
increase if the mental workload increases while saccade distance and saccade
speed do not show any significant differences. This assessment of mental
workload could be a trigger for aiding the operator of an information system,
in order to meet operational requirements. Keywords: mental workload; adaptive automation; eye movement; pupil diameter; saccade;
fixation time | |||
| Impact of Automation and Task Load on Unmanned System Operator's Eye Movement Patterns | | BIBAK | Full-Text | 229-238 | |
| Cali M. Fidopiastis; Julie M. Drexler; Daniel Barber; Keryl Cosenzo; Michael J. Barnes; Jessie Y. C. Chen; Denise M. Nicholson | |||
| Eye tracking under naturalistic viewing conditions may provide a means to
assess operator workload in an unobtrusive manner. Specifically, we explore the
use of a nearest neighbor index of workload calculated using eye fixation
patterns obtained from operators navigating an unmanned ground vehicle under
different task loads and levels of automation. Results showed that fixation
patterns map to the operator's experimental condition suggesting that
systematic eye movements may characterize each task. Further, different methods
of calculating the workload index are highly correlated, r(46) = .94, p = .01.
While the eye movement workload index matches operator reports of workload
based on the NASA TLX, the metric fails on some instances. Interestingly, these
departure points may relate to the operator's perceived attentional control
score. We discuss these results in relation to automation triggers for unmanned
systems. Keywords: Adaptive Automation; Unmanned Ground Systems; Eye Tracking; Workload | |||
| Combining Electroencephalograph and Functional Near Infrared Spectroscopy to Explore Users' Mental Workload | | BIBAK | Full-Text | 239-247 | |
| Leanne M. Hirshfield; Krysta Chauncey; Rebecca Gulotta; Audrey Girouard; Erin Treacy Solovey; Robert J. K. Jacob; Angelo Sassaroli; Sergio Fantini | |||
| We discuss the physiological metrics that can be measured with
electroencephalography (EEG) and functional near infrared spectroscopy (fNIRs).
We address the functional and practical limitations of each device, and
technical issues to be mindful of when combining the devices. We also present
machine learning methods that can be used on concurrent recordings of EEG and
fNIRs data. We discuss an experiment that combines fNIRs and EEG to measure a
range of user states that are of interest in HCI. While our fNIRS machine
learning results showed promise for the measurement of workload states in HCI,
our EEG results indicate that more research must be done in order to combine
these two devices in practice. Keywords: fNIRs; EEG; near infrared spectroscopy; workload | |||
| Detecting Intentional Errors Using the Pressures Applied to a Computer Mouse | | BIBAK | Full-Text | 248-253 | |
| Curtis S. Ikehara; Martha E. Crosby | |||
| Intentional errors are considered a form of deceit. In this pilot study, the
pressures applied to a computer mouse will be analyzed to determine if it is
possible to detect intentional errors. Twenty participants ranging in age from
18 to 21 years performed a task involving intentionally making errors when
instructed. A comparison will be made between the pressures applied to a
computer mouse when answering the questions with the intention of being correct
and with the intention of making an error. The data will need to be normalized
for each individual to obtain accurate results. The analysis of the pressures
may indicate that there are detectable variations within some individuals. Due
to the preliminary nature of this study further research will be required. Keywords: Intentional errors; deceit; pressure sensitive computer mouse | |||
| Visual Navigation Patterns and Cognitive Load | | BIBAK | Full-Text | 254-259 | |
| Laurel A. King | |||
| Eye tracking technology is a prospective tool for augmenting cognition in
real-time in response to screen navigation and other eye movements that can be
monitored. This paper examines eye movements associated with differences in
problem complexity. The experiment utilized constraint satisfaction problems of
differing difficulty measured by the number of steps necessary to complete and
the relative time required to solve it. Participants were observed and tested
through an eye-tracking experiment to see if correlations between visual
navigation and problem complexity were present. Eye movement patterns, in
particular pupil size, have been used to measure cognitive load in other
contexts [6-9]. The results showed overall increases in fixations and pupil
size that corresponded to increases in problem complexity. Keywords: Cognitive load; eye tracking; analytical reasoning | |||
| Modeling the Cognitive Task Load and Performance of Naval Operators | | BIBAK | Full-Text | 260-269 | |
| Mark A. Neerincx; Stefan Kennedie; Marc Grootjen; Franc Grootjen | |||
| Operators on naval ships have to act in dynamic, critical and high-demand
task environments. For these environments, a cognitive task load (CTL) model
has been proposed as foundation of three operator support functions: adaptive
task allocation, cognitive aids and resource feedback. This paper presents the
construction of such a model as a Bayesian network with probability
relationships between CTL and performance. The network is trained and tested
with two datasets: operator performance with an adaptive user interface in a
lab-setting and operator performance on a high-tech sailing ship. The
"Naïve Bayesian network" tuned out to be the best choice, providing
performance estimations with 86% and 74% accuracy for respectively the lab and
ship data. Overall, the resulting model nicely generalizes over the two
datasets. It will be used to estimate operator performance under momentary
CTL-conditions, and to set the thresholds of the load-mitigation strategies for
the three support functions. Keywords: mental load; emotion; Bayesian networks; cognitive engineering; Defense and
Space operations | |||
| Impact on Performance and Process by a Social Annotation System: A Social Reading Experiment | | BIBAK | Full-Text | 270-278 | |
| Les Nelson; Gregorio Convertino; Peter Pirolli; Lichan Hong; Ed H. Chi | |||
| Social annotation systems such as SparTag.us and del.icio.us have been
designed to encourage individual reading and marking behaviors that, when
shared, accumulate to build collective knowledge spaces. Prior work reported on
the experimental design and performance effects observed in a controlled study
of SparTag.us. Study participants working independently on a sensemaking task
who had access to a set of expert annotations were compared against
participants using SparTag.us without those annotations and participants using
only office software for annotation support. A learning effect favored the
participants exposed to expert annotations. In this paper, we analyze the
behavioral data captured during the experiment and identify differences in the
work process that can explain the performance effects reported previously. Keywords: Convergent measures; social annotation systems; evaluation; social
sensemaking | |||
| Proposing Strategies to Prevent the Human Error in Automated Industrial Environments | | BIBAK | Full-Text | 279-288 | |
| José A. do N. Neto; Maria de Fátima Queiroz Vieira; Charles Santoni; Daniel Scherer | |||
| This paper presents a process to conceive strategies to prevent the human
error when operating industrial systems. The process adopts a broader view to
error prevention, going beyond the error analysis to consider the user profile,
the task and context description. The error classification is done according to
a task execution cognitive model. The conceived strategies focus on the human
interface component of those systems since it is this work's premise that the
human interface design has a strong impact on the human error rate. Keywords: Human-Machine Interfaces; Human error; Cognitive model | |||
| Wearable Modular Device for Facilitation of Napping and Optimization of Post-nap Performance | | BIBAK | Full-Text | 289-298 | |
| Djordje Popovic; Giby Raphael; Robin Johnson; Gene Davis; Chris Berka | |||
| Sleep deprivation-induced deficiencies in performance can be associated with
high financial and human costs. Napping is an effective countermeasure, but the
effects depend on previously accumulated sleep debt and timing, duration and
sleep architecture of the naps. Long-term assessment of sleep architecture of
nap/sleep episodes could yield an estimate of the accumulated sleep debt and
help optimize the napping schedule. Moreover, sensory stimulation coupled with
real-time assessment of sleep states could optimize sleep architecture and
duration of each nap. With these goals in mind we designed a wearable device,
dubbed Nap Cap, which integrates real-time EEG analysis with audio, visual and
thermal stimulation. The prototype was evaluated on seven subjects (fully
rested vs. sleep-deprived). While the prototype provided high quality EEG and
comfort, sensory stimulation did not significantly influence sleep
architecture. Evaluation of more paradigms of sensory stimulation on larger
samples is warranted before final conclusions can be made. Keywords: Nap; Sleep Deprivation; Performance Optimization; Wearable Devices | |||
| Converging Minds: Assessing Team Performance Using Psychophysiological Measures | | BIBAK | Full-Text | 299-303 | |
| Aniket A. Vartak; Siddharth S. Somvanshi; Cali M. Fidopiastis; Denise M. Nicholson | |||
| Effective teams are an integral component to the success and the advancement
of any organization. This issue emphasizes the need to develop valid measures
for team performance especially in operational environments. The use of
psychophysiological data has been proposed as a candidate for developing these
team-level measures. In this paper, we review past research in the field and
discuss two contrasting approaches to model human cognition used in the context
of teams. We then propose a test-bed for evaluating these models for
human-in-the loop adaptive systems using psychophysiological measures. Keywords: Team Performance; Team Cognition; Psychophysiology; Social Cybernetics;
Information Processing; Closed-Loop Human Systems | |||
| Measuring Cognitive Workload in Non-military Scenarios Criteria for Sensor Technologies | | BIBAK | Full-Text | 304-310 | |
| Jörg Voskamp; Bodo Urban | |||
| Augmented Cognition manifesting in the DARPA project is becoming of more and
more interest to non-military application areas. First areas it is going to be
applied are in flight control and power plant control. Measuring cognitive
workload in the context of Augmented Cognition is bound to the application of
sensor technologies and frameworks which are going to be applied to users. It
is necessary to make Augmented Cognition Application in non-military areas as
comfortable to the user as possible as we do not want to disturb her but to
support her in her tasks. In this paper we will define criteria to be
considered when designing Augmented Cognition applications in non-military
environments. Keywords: Augmented Cognition; Application; Sensors systems; sensor criteria | |||
| Combined Effects of Sleep Deprivation, Narrow Space, Social Isolation and High Cognitive Workload on Cognitive Ability of Chinese Operators | | BIBAK | Full-Text | 311-316 | |
| Yijing Zhang; Xueyong Liu; Zhizhong Li; Bin Wu; Fang Liu; Xiaolu Jing; Jun Wang; Haibo Qin; Su Wu | |||
| This study aims to investigate the effects of sleep deprivation on the
cognitive abilities of Chinese subjects under a combined scenario of narrow
space, social isolation, and high cognitive workload. Twelve subjects
participated in the experiment of 72-hour sleep deprivation, and took 15
cognitive ability tests for three times at the first day of sleep deprivation
(level 1), the second day of sleep deprivation (level 2) and the third day of
sleep deprivation (level 3) respectively. The result data analyses show that:
most of the cognitive abilities do not change significantly, but the value of
special graphics search is increased significantly with the increasing of sleep
deprivation time (p=0.01). In addition, when four cognitive ability tests were
combined into one complex measure, the effect of sleep deprivation becomes more
significant. The results mainly support the Hockey's compensatory control
model. And they may be due to two other reasons: one is that the combined
stressors will counteract each other; the other is that learning effect can
improve operators' performance. The results also imply that sensitive and
complex measures need to be developed and used to reflect the compound effects
of sleep deprivation under such combined situation. Keywords: Sleep deprivation; narrow space; social isolation; high cognitive workload;
cognitive ability | |||
| Quantifying the Feasibility of Compressive Sensing in Portable Electroencephalography Systems | | BIBAK | Full-Text | 319-328 | |
| Amir M. Abdulghani; Alexander J. Casson; Esther Rodríguez-Villegas | |||
| The EEG for use in augmented cognition produces large amounts of
compressible data from multiple electrodes mounted on the scalp. This huge
amount of data needs to be processed, stored and transmitted and consumes large
amounts of power. In turn this leads to physically large EEG units with limited
lifetimes which limit the ease of use, and robustness and reliability of the
recording. This work investigates the suitability of compressive sensing, a
recent development in compression theory, for providing online data reduction
to decrease the amount of system power required. System modeling which
incorporates a review of state-of-the-art EEG suitable integrated circuits
shows that compressive sensing offers no benefits when using an EEG system with
only a few channels. It can, however, lead to significant power savings in
situations where more than approximately 20 channels are required. This result
shows that the further investigation and optimization of compressive sensing
algorithms for EEG data is justified. Keywords: Compressive Sensing; Electroencephalogram; Power efficient; Wireless Systems | |||
| Are You Really Looking? Finding the Answer through Fixation Patterns and EEG | | BIBA | Full-Text | 329-338 | |
| Anne-Marie Brouwer; Maarten A. Hogervorst; Pawel Herman; Frank Kooi | |||
| Eye movement recordings do not tell us whether observers are 'really looking' or whether they are paying attention to something else than the visual environment. We want to determine whether an observer's main current occupation is visual or not by investigating fixation patterns and EEG. Subjects were presented with auditory and visual stimuli. In some conditions, they focused on the auditory information whereas in others they searched or judged the visual stimuli. Observers made more fixations that are less cluttered in the visual compared to the auditory tasks, and they were less variable in their average fixation location. Fixated features revealed which target the observers were looking for. Gaze was not attracted more by salient features when performing the auditory task. 8-12 Hz EEG oscillations recorded over the parieto-occipital regions were stronger during the auditory task than during visual search. Our results are directly relevant for monitoring surveillance workers. | |||
| "What Was He Thinking?": Using EEG Data to Facilitate the Interpretation of Performance Patterns | | BIBAK | Full-Text | 339-347 | |
| Gwendolyn E. Campbell; Christine L. Belz; Phan Luu | |||
| Previous research has demonstrated that EEG data can be used to identify and
remove unintentional responses from a data set (guesses and slips). This study
sought to determine if removing this error variance has a significant impact on
the interpretation of a trainee's performance. Participants were taught to
recognize tank silhouettes. Multiple linear regression models were built for
each participant based on three sets of their data: 1) all trials of their
performance data, 2) only trials that were learned according to a state space
analysis, and 3) their intentional data as identified by EEG. When compared to
an expert model, each of the three models for every participant yielded a
different diagnosis, indicating that filtering performance data with EEG data
changes the interpretation of a participant's competence. Keywords: electroencephalography; training; student modeling | |||
| Motion-Sickness Related Brain Areas and EEG Power Activates | | BIBAK | Full-Text | 348-354 | |
| Yu-Chieh Chen; Jeng-Ren Duann; Chun-Ling Lin; Shang-Wen Chuang; Tzyy-Ping Jung; Chin-Teng Lin | |||
| This study investigates electroencephalographic (EEG) correlates of motion
sickness in a virtual-reality based driving simulator. The driving simulator
comprised an actual automobile mounted on a Stewart motion platform with six
degrees of freedom, providing both visual and vestibular stimulations to induce
motion-sickness in a manner that is close to that in daily life. EEG data were
acquired at a sampling rate of 500 Hz using a 32-channel EEG system. The
acquired EEG signals were analyzed using independent component analysis (ICA)
and time-frequency analysis to assess EEG correlates of motion sickness.
Subject's degree of motion-sickness was simultaneously and continuously
reported using an onsite joystick, providing non-stop psychophysical references
to the recorded EEG changes. Five Motion-sickness related brain processes with
equivalent dipoles located in the left motor, the parietal, the right motor,
the occipital and the occipital midline areas were consistently identified
across all subjects. These components exhibited distinct spectral suppressions
or augmentation in motion sickness. The results of this study could lead to a
practical human-machine interface for noninvasive monitoring of motion sickness
of drivers or passengers in real-world environments. Keywords: EEG; ICA; motion-sickness; delta; theta; alpha; time-frequency | |||
| Building Dependable EEG Classifiers for the Real World -- It's Not Just about the Hardware | | BIBAK | Full-Text | 355-364 | |
| Gene Davis; Djordje Popovic; Robin R. Johnson; Chris Berka; Mirko Mitrovic | |||
| One of the major deficiencies with the EEG-based classifiers used in today's
laboratory settings is that they are often ill suited for the real world. In
many cases the classifiers that were painstakingly developed in the controlled
laboratory environment become unreliable with increased mobility of the user.
In addition to increased mobility, many real world scenarios impose constraints
on data collection that cannot be accommodated by the lab-created classifier.
Addressing these issues throughout the development process of EEG-based
classifiers by building hardware, software, and algorithms intended for use in
the real world should result in more dependable classifiers. With this approach
we were able to collect and classify data on a research vessel at sea, in the
desert by night, on dismounted soldiers in the training field, and everywhere
between. Keywords: Electroencephalogram (EEG); Mobile EEG; Operational Neuroscience;
Engagement; Workload; Drowsiness | |||
| Improved Team Performance Using EEG- and Context-Based Cognitive-State Classifications for a Vehicle Crew | | BIBA | Full-Text | 365-372 | |
| Kevin R. Dixon; Konrad Hagemann; Justin Basilico; J. Chris Forsythe; Siegfried Rothe; Michael Schrauf; Wilhelm E. Kincses | |||
| We present an augmented cognition (AugCog) system that utilizes two sources
to assess cognitive state as a basis for actions to improve operator
performance. First, continuous EEG is measured and signal processing algorithms
utilized to identify patterns of activity indicative of high cognitive demand.
Second, data from the automobile is used to infer the ongoing driving context.
Subjects participated as eleven 2-person crews consisting of a driver/
navigator and a commander/gunner. While driving a closed-loop test route, the
driver received through headphones a series of communications and had to
perform two secondary tasks. Certain segments of the route were designated as
threat zones. The commander was alerted when entering a threat zone and their
task was to detect targets mounted on the roadside and engage those targets To
determine targeting success, a photo was taken with each activation of the
trigger and these photos were assessed with respect to the position of the
reticle relative to the target. In a secondary task, the commander was
presented a series of communications through headphones. Our results show that
it is possible to reliably discriminate different cognitive states on the basis
of neuronal signals. Results also confirmed our hypothesis: improved
performance at the crew level in the AugCog condition for a secondary
communications tasks, as compared to a control condition, with no change in
performance for the primary tasks. Note: Best Paper Award | |||
| Detecting Frontal EEG Activities with Forehead Electrodes | | BIBAK | Full-Text | 373-379 | |
| Jeng-Ren Duann; Po-Chuan Chen; Li-Wei Ko; Ruey-Song Huang; Tzyy-Ping Jung; Chin-Teng Lin | |||
| This study demonstrates the acquisitions of EEG signals from non-hairy
forehead sites and tested the feasibility of using the forehead EEG in
detecting drowsiness-related brain activities. A custom-made 15-channel
forehead EEG-electrode patch and 28 scalp electrodes placed according to the
International 10-20 system were used to simultaneously record EEG signals from
the forehead and whole-head regions, respectively. A total of five subjects
were instructed to perform a night-time long-haul driving task for an hour in a
virtual-reality based driving simulator comprising a real car mounted on a 6
degree-of-freedom Steward motion platform and a immersive VR environment with
360 degree projection scenes. Separate independent component analyses were
applied to the forehead and whole-head EEG data for each individual subject.
For the whole-head independent component (IC) set, the frontal central midline
(FCM) IC with an equivalent dipole source located in the anterior cingulate
cortex was selected for further analysis. For the forehead IC set, the IC with
its theta power changes highly correlated with subject's driving performance
was selected. The EEG power changes of the selected forehead ICs were then used
to predict driving performance based on a linear regression model. The results
of this study showed that it is feasible to accurately estimate quantitatively
the changing level of driving performance using the EEG features obtained from
the forehead non-hairy channels, and the estimation accuracy was comparable to
that using the EEG features of the whole-head recordings. Keywords: Forehead EEG; Drowsiness; Driving performance; Independent component
analysis (ICA) | |||
| The Effectiveness of Feedback Control in a HCI System Using Biological Features of Human Beings | | BIBAK | Full-Text | 380-389 | |
| Mariko Fujikake Funada; Miki Shibukawa; Yoshihide Igarashi; Takashi Shimizu; Tadashi Funada; Satoki P. Ninomija | |||
| The purpose of this paper is to clarify the brain activities of human beings
engaged in their tasks. Response time, correctness ratios, and Event Related
Potentials (ERPs) are useful indexes of the brain activities of a subject at
his task in the experiments. We analyze these indexes by a method called the
Principle Component Analysis. Then we characterize the brain activities while
he is engaged in the task. Finally we discuss the effectiveness of feedback
control in a HCI system using these indexes. Keywords: event related potentials; feedback control; principle component analysis;
response time | |||
| Bayesian Reconstruction of Perceptual Experiences from Human Brain Activity | | BIBAK | Full-Text | 390-393 | |
| Jack L. Gallant; Thomas Naselaris; Ryan J. Prenger; Kendrick N. Kay; Dustin Stansbury; Michael Oliver; An Vu; Shinji Nishimoto | |||
| A method for decoding the subjective contents of perceptual systems in the
human brain would have broad practical utility for communication and as a
brain-machine interface. Previous approaches to this problem in vision have
used linear classifiers to solve specific problems, but these approaches were
not general enough to solve complex problems such as reconstructing subjective
perceptual states. We have developed a new approach to these problems based on
quantitative encoding models that explicitly describe how visual stimuli are
(nonlinearly) transformed into brain activity. We then invert these encoding
models in order to decode activity evoked by novel images or movies, providing
reconstructions with unprecedented fidelity. Here we briefly review these
results and the potential uses of perceptual decoding devices. Keywords: Bayesian; vision; brain-machine interface; brain-computer interface; brain
reading | |||
| Tonic Changes in EEG Power Spectra during Simulated Driving | | BIBAK | Full-Text | 394-403 | |
| Ruey-Song Huang; Tzyy-Ping Jung; Scott Makeig | |||
| Electroencephalographic (EEG) correlates of driving performance were studied
using an event-related lane-departure paradigm. High-density EEG data were
analyzed using independent component analysis (ICA) and Fourier analysis.
Across subjects and sessions, when reaction time to lane-departure events
increased, several clusters of independent component activities in the
occipital, posterior parietal, and middle temporal cortex showed tonic power
increases in the delta, theta, and alpha bands. The strongest of these tonic
power increases occurred in the alpha band in the occipital and parietal
regions. Other independent component clusters in the somatomotor and frontal
regions showed less or no significant increase in all frequency bands as RT
increased. This study demonstrates additional evidence of the close and
specific links between cortical brain activities (via changes in EEG spectral
power) and performance (reaction time) during sustained-attention tasks. These
results may also provide insights into the development of human-computer
interfaces for countermeasures for drowsy driving. Keywords: EEG; ICA; driving; alertness; delta; theta; alpha; reaction time | |||
| P300 Based Single Trial Independent Component Analysis on EEG Signal | | BIBA | Full-Text | 404-410 | |
| Kun Li; Ravi Sankar; Yael Arbel; Emanuel Donchin | |||
| A Brain Computer Interface (BCI) is a device that allows the user to communicate with the world without utilizing voluntary muscle activity (i.e., using only the electrical activity of the brain). It makes use of the well-studied observation that the brain reacts differently to different stimuli, as a function of the level of attention allotted to the stimulus stream and the specific processing triggered by the stimulus. In this article we present a single trial independent component analysis (ICA) method that is working with a BCI system proposed by Farwell and Donchin. It can dramatically reduce the signal processing time and improve the data communicating rate. This ICA method achieved 76.67% accuracy on single trial P300 response identification. | |||
| Directed Components Analysis: An Analytic Method for the Removal of Biophysical Artifacts from EEG Data | | BIBAK | Full-Text | 411-416 | |
| Phan Luu; Robert Frank; Scott Kerick; Don M. Tucker | |||
| Artifacts generated by biophysical sources (such as muscles, eyes, and
heart) often hamper the use of EEG for the study of brain functions in basic
research and applied settings. These artifacts share frequency overlap with the
EEG, making frequency filtering inappropriate for their removal. Spatial
decomposition methods, such as principal and independent components analysis,
have been employed for the removal of the artifacts from the EEG. However,
these methods have limitations that prevent their use in operational
environments that require real-time analysis. We have introduced a directed
components analysis (DCA) that employs a spatial template to direct the
selection of target artifacts. This method is computationally efficient,
allowing it to be employed in real-world applications. In this paper, we
evaluate the effect of spatial undersampling of the scalp potential field on
the ability of DCA to remove blink artifacts. Keywords: EEG; artifact; brain activity; neuroergonomic | |||
| Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach | | BIBAK | Full-Text | 417-426 | |
| Anna C. Merzagora; Meltem Izzetoglu; Robi Polikar; Valerie Weisser; Banu Onaral; Maria T. Schultheis | |||
| Although neuroimaging has greatly expanded our knowledge about the
brain-behavior relation, combining multiple neuroimaging modalities with
complementing strengths can overcome some limitations encountered when using a
single modality. Valuable candidates for a multimodal approach are functional
near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). fNIRS is
an imaging technology that localizes hemodynamic changes within the cortex.
However, hemodynamic activation is an intrinsically slow process. On the other
hand, EEG has excellent time resolution by directly measuring the manifestation
of the brain electrical activity at the scalp. Based on their complementary
strengths, the integration of fNIRS and EEG may provide higher spatiotemporal
resolution than either method alone. In this effort, we integrate fNIRS and EEG
to evaluate the behavioral performance of six healthy adults in a working
memory task. To this end, features extracted from fNIRS and EEG were used
separately, as well as in combination, and their performances were compared
against each other. Keywords: multimodal neuroimaging; functional near-infrared spectroscopy; EEG; pattern
classification; working memory; n-back; P300 | |||
| Transcranial Doppler: A Tool for Augmented Cognition in Virtual Environments | | BIBAK | Full-Text | 427-436 | |
| Beatriz Rey; Mariano Alcañiz Raya; Valery Naranjo; José Tembl; Vera Parkhutik | |||
| In this work, we propose the use of Transcranial Doppler Monitoring (TCD) as
a tool to measure brain activity during the exposure to virtual environments
(VE) that can be used in Augmented Cognition (AugCog) systems. The technique is
non-invasive, and can be easily integrated with virtual reality (VR) settings.
Its high temporal resolution allows the correlation of changes in brain
activity to specific events in the VE. In this paper, the TCD technique is
described, and results from two studies developed in our group combining TCD
with VR are summarized. Possible applications of TCD in the AugCog field are
finally discussed. Keywords: Augmented Cognition; Virtual Reality; Transcranial Doppler;
Neurophysiological Data; Cognitive State Assessment | |||
| Predicting Intended Movement Direction Using EEG from Human Posterior Parietal Cortex | | BIBAK | Full-Text | 437-446 | |
| Yijun Wang; Scott Makeig | |||
| The posterior parietal cortex (PPC) plays an important role in motor
planning and execution. Here, we investigated whether noninvasive
electroencephalographic (EEG) signals recorded from the human PPC can be used
to decode intended movement direction. To this end, we recorded whole-head EEG
with a delayed saccade-or-reach task and found direction-related modulation of
event-related potentials (ERPs) in the PPC. Using parietal EEG components
extracted by independent component analysis (ICA), we obtained an average
accuracy of 80.25% on four subjects in binary single-trial EEG classification
(left versus right). These results show that in the PPC, neuronal activity
associated with different movement directions can be distinguished using EEG
recording and might, thus, be used to drive a noninvasive brain-machine
interface (BMI). Keywords: posterior parietal cortex (PPC); electroencephalography (EEG); independent
component analysis (ICA); brain-machine interface (BMI) | |||
| Enhancing Text-Based Analysis Using Neurophysiological Measures | | BIBAK | Full-Text | 449-458 | |
| Adrienne Behneman; Natalie Kintz; Robin Johnson; Chris Berka; Kelly S. Hale; Sven Fuchs; Par Axelsson; Angela Baskin | |||
| Intelligence analysts are faced with the demanding task of identifying
patterns in large volumes of complex, textual sources and predicting possible
outcomes based on perceived patterns. To address this need, the Advanced
Neurophysiology for Intelligence Text Analysis (ANITA) system is being
developed to provide a real-time analysis system using EEG to monitor analysts'
processing of textual data during evidence gathering. Both conscious and
unconscious 'interest' are identified by the neurophysiological sensors based
on the analyst's mental model, as related to specific sentences, indicating
relevance to the analysis goal. By monitoring the evidence gathering process
through neurophysiological sensors and implementation of real-time strategies,
more accurate and efficient extraction of evidence may be achieved. This paper
outlines an experiment that focused on identifying distinct changes in EEG
signals that can be used to decipher sentences of relevance versus those of
irrelevance to a given proposition. Keywords: EEG; Reading; Relevancy; Alpha; Theta | |||
| Affective Computer-Generated Stimulus Exposure: Psychophysiological Support for Increased Elicitation of Negative Emotions in High and Low Fear Subjects | | BIBAK | Full-Text | 459-468 | |
| Christopher G. Courtney; Michael E. Dawson; Anne M. Schell; Thomas D. Parsons | |||
| The present study examined physiological measures of affect when viewing
images from the International Affective Picture System (IAPS),
computer-generated still images, and computer-generated videos of feared and
non-feared stimuli. Twenty low fear (LF) and twelve high fear (HF) individuals
viewed static and moving images of spiders and snakes. In both LF and HF
subjects, computer-generated video images elicited more intense affective
responses than the IAPS images and the computer-generated stills.
Computer-generated still images were as effective in eliciting fear responses
as the IAPS. These results suggest that computer-generated images can be as or
more effective as the IAPS in eliciting fear. Regardless of modality, HF
subjects showed stronger physiological responses to their specifically feared
stimulus (snake or spider) than to a non-feared stimulus. Keywords: Psychophysiology; Fear; EMG; skin conductance; VR; startle | |||
| Applying Real Time Physiological Measures of Cognitive Load to Improve Training | | BIBA | Full-Text | 469-478 | |
| Joseph T. Coyne; Carryl Baldwin; Anna Cole; Ciara Sibley; Daniel M. Roberts | |||
| This paper discusses how the fields of augmented cognition and neuroergonomics can be expanded into training. Several classification algorithms based upon EEG data and occular data are discussed in terms of their ability to classify operator state in real time. These indices have been shown to enhance operator performance within adaptive automation paradigms. Learning is different from performing a task that one is familiar with. According to cognitive load theory (CLT), learning is essentially the act of organizing information from working memory into long term memory. However, our working memory system has a bottleneck in this process, such that when training exceeds working memory capacity, learning is hindered. This paper discusses how CLT can be combined with multiple resource theory to create a model of adaptive training. This new paradigm hypothesizes that a system that can monitor working memory capacity in real time and adjust training difficulty can improve learning. | |||
| Considerations for Designing Response Quantification Procedures in Non-traditional Psychophysiological Applications | | BIBA | Full-Text | 479-487 | |
| A. V. Iyer; L. D. Cosand; Christopher G. Courtney; Albert A. Rizzo; Thomas D. Parsons | |||
| Psychophysiological assessment in the context of virtual environments is a promising means for benchmarking the efficacy and ecological validity of virtual reality scenarios. When applied to human-computer interaction, psychophysiological and affective computing approaches may increase facility for development of the next generation of human-computer systems. Such systems have the potential to use psychophysiological signals for user-feedback and adaptive responding. As the composition of investigating teams becomes diverse in keeping with interdisciplinary trends, there is a need to review de-facto standards of psychophysiological response quantification and arrive at consensus protocols adequately addressing the concerns of basic researchers and application developers. The current paper offers a demonstration of the ways in which such consensus scoring protocols may be derived. Electromyographic eye-blink scoring from an immersion investigation is used as an illustrative case study. | |||
| Neurophysiological Measures of Brain Activity: Going from the Scalp to the Brain | | BIBAK | Full-Text | 488-494 | |
| Phan Luu; Catherine Poulsen; Don M. Tucker | |||
| Behavior, such as reaction time and correctness of a response, is the most
studied output of the mind in the fields of psychology and human factors. With
the advent of modern neuroimaging technologies, opportunities exist for direct
study of the mind's machinery: the brain. Moreover, there are opportunities for
applying these technologies to solve a host of educational and engineering
challenges, such as how to design better interfaces with computer systems or
how to better educate and train students. The electroencephalogram (EEG) is a
direct reflection of the functioning brain, and technologies that enable
recording of the EEG have been in existence for more than 50 years. Within the
past decade substantial progress has been made in EEG technology, permitting a
direct view into the brain. We cover these advances in this paper, which
include dense-sensor array technology and physics-based computational head
models, and present several examples of how they have been applied. Keywords: Dense-Array EEG; neuroergonomic | |||
| Parsimonious Identification of Physiological Indices for Monitoring Cognitive Fatigue | | BIBAK | Full-Text | 495-503 | |
| Lance J. Myers; J. Hunter Downs | |||
| The objective of this study was to identify a parsimonious set of
physiological measures that could be used to best predict cognitive fatigue
levels. A 37 hour sleep deprivation study was conducted to induce reduced
levels of alertness and cognitive impairment as measured by a psychomotor
vigilance test. Non-invasive, wearable and ambulatory sensors were used to
acquire cardio-respiratory and motion data during the sleep deprivation.
Subsequently 23 potential predictors were derived from the raw sensor data. The
least absolute shrinkage and selection operator, along with a cross validation
strategy was used to create a sparse model and identify a minimum predictor
subset that provided the best prediction accuracy. Final predictor selection
was found to vary with task and context. Depending on context selected
predictors indicated elevated levels of sympathetic nervous system activity,
increased restlessness during engaging tasks and increased cardio-respiratory
synchronization with increasing cognitive fatigue. Keywords: cognitive fatigue; heart rate variability; feature selection; wearable
sensors | |||
| In-Helmet Oxy-hemoglobin Change Detection Using Near-Infrared Sensing | | BIBAK | Full-Text | 504-513 | |
| Erin M. Nishimura; Christopher A. Russell; J. Patrick Stautzenberger; Harvey Ku; J. Hunter Downs | |||
| Near-infrared (NIR) sensing in flight applications can provide critical
objective indicators of crew state. By monitoring oxy-hemoglobin
concentrations, a NIR sensor can detect changes in flight crew physiology in
response to both cognitive demands and extreme conditions related to flight
applications, including gravity-induced loss of consciousness (G-LOC) and
hypoxia. A custom NIR sensor was created for in-helmet monitoring of
oxy-hemoglobin in flight. This wearable, wireless sensor addresses requirements
for flight applications and was applied to a case study that examines the raw
optical signal and oxy-hemoglobin response to Valsalva maneuvers performed at
1g. Keywords: Near-infrared sensing; functional brain imaging; oxy-hemoglobin;
hemodynamics; physiologic monitoring | |||
| Assessment of Psychophysiological Differences of West Point Cadets and Civilian Controls Immersed within a Virtual Environment | | BIBAK | Full-Text | 514-523 | |
| Thomas D. Parsons; Christopher G. Courtney; Louise Cosand; Arvind Iyer; Albert A. Rizzo; Kelvin S. Oie | |||
| An important question for ecologically valid virtual environments is whether
cohort characteristics affect immersion. If a method for assessing a certain
neurocognitive capacity (e.g. attentional processing) is adapted to a cohort
other than the one that was used for the initial normative distribution, data
obtained in the new cohort may not be reflective of the neurocognitive capacity
in question. We assessed the psychophysiological impact of different levels of
immersion upon persons from two cohorts: 1) civilian university students; and
2) West Point Cadets. Cadets were found to have diminished startle eyeblink
amplitude compared with civilians, which may reflect that cadets experienced
less negative affect during the scenario in general. Further, heart rate data
revealed that Cadets had significantly lower heart rates than Civilians in the
"low" but not "high" immersion condition. This suggests that "low" immersion
conditions may not have the ecological validity necessary to evoke consistent
affect across cohorts. Keywords: virtual environment; psychophysiological assessment; immersion; ecological
validity; neuropsychology | |||
| Characterizing the Psychophysiological Profile of Expert and Novice Marksmen | | BIBAK | Full-Text | 524-532 | |
| Nicholas Pojman; Adrienne Behneman; Natalie Kintz; Robin Johnson; Gregory K. W. K. Chung; Sam O. Nagashima; Paul Espinosa; Chris Berka | |||
| Marksmanship training includes a combination of classroom instruction and
field practice involving the instantiation of a well-defined set of sensory,
motor, and cognitive skills. 10 expert marksmen and 30 novices participated in
a study that measured marksman performance during simulated ballistics shooting
of a M4 replica infrared rifle. Participants' physiology and performance were
quantified while they completed a battery of neurocognitive tests. Experts
demonstrated consistent and more accurate shot performance across all trials.
Compared to novices, experts evidenced lower levels of sympathetic activation
as measured by heart rate variability during the neurocognitive tasks. Factor
analysis identified experts as having above normal visuospatial processing
speeds and sustained attention, reflecting experts as having better performance
during vigilance neurocognitive tasks. Identifying physiological metrics of
experts during neurocognitive testing opens the door to individualized novice
instruction to help to improve specific areas flagged as below normal during or
prior to novice marksmanship instruction. Keywords: Electroencephalogram (EEG); Electrocardiogram (EKG); Marksmanship; Expert;
Heart Rate Variability; Neurocognitive testing; psychomotor skill acquisition | |||
| Assessing Cognitive State with Multiple Physiological Measures: A Modular Approach | | BIBAK | Full-Text | 533-542 | |
| Lee W. Sciarini; Denise M. Nicholson | |||
| The purpose of this effort is to introduce a novel approach which can be
used to determine how multiple minimally intrusive physiological sensors can be
used together and validly applied to areas such as Augmented Cognition and
Neuroergonomics. While researchers in these fields have established the utility
of many physiological measures for informing when to adapt systems, the use of
such measures together remains limited. Specifically, this effort will provide
a contextual explanation of cognitive state, workload, and the measurement of
both; provide a brief discussion on several relatively noninvasive
physiological measures; explore what a modular cognitive state gauge should
consist of; and finally, propose a framework based on the previous items that
can be used to determine the interactions of the various measures in relation
to the change of cognitive state. Keywords: Augmented Cognition; Neuroergonomics; Physiological Measures | |||
| Neuro-NIRS: Analysis of Neural Activities Using NIRS | | BIBAK | Full-Text | 543-552 | |
| Hiroshi Tamura; Miki Fuchigami; Akira Okada | |||
| Analysis method for quick component of NIRS is explained. In order to
compare quantitatively the amount of quick component, absolute average
operation is applied. The result Q is then formulated as the product of
magnitude M and density D. By characteristic differences of M and D functional
features of each channel are discussed. The method is applied to text entry
task to mobile phone. Most of 34 channels under study D values diverged in rest
state, but they converged at task state. 6 channels among 34, showed specific
responses to specific task. Keywords: neural activities; NIRS; quick components; text entry; mobile phone | |||
| Eye Movements and Pupil Size Reveal Deception in Computer Administered Questionnaires | | BIBAK | Full-Text | 553-562 | |
| Andrea K. Webb; Douglas J. Hacker; Dahvyn Osher; Anne E. Cook; Dan J. Woltz; Sean Kristjansson; John C. Kircher | |||
| An oculomotor test is described that uses pupil diameter and eye movements
during reading to detect deception. Forty participants read and responded to
statements on a computerized questionnaire about their possible involvement in
one of two mock crimes. Twenty guilty participants committed one of two mock
crimes, and 20 innocent participants committed no crime. Guilty participants
demonstrated speeded and accurate reading when they encountered statements
about their crime and increases in pupil size. A discriminant function of
oculomotor measures successfully discriminated between guilty and innocent
participants and between the two groups of guilty participants. Results suggest
that oculomotor tests may be of value for pre-employment and security screening
applications. Keywords: Oculomotor measures; pupil size; deception | |||
| Physiological-Based Assessment of the Resilience of Training to Stressful Conditions | | BIBAK | Full-Text | 563-571 | |
| Mikhail Zotov; J. Forsythe; Vladimir Petrukovich; Inga Akhmedova | |||
| Russian applied psychophysiology has a wide experience of using the heart
rate variability (HRV) measures for the assessment of operator workload.
However, 'workload indexes' that have received a wide practical application,
such as tension index (TI), are not sensitive to the moment-to-moment changes
of operator physiological arousal level during the performance of cognitive
tasks. In this connection, a new method of HRV analysis called CS-index is
offered. This index permits to identify moment-to-moment changes of operator's
functional state. The presented research shows that CS-index is sensitive to
task load factors, such as task difficulty level and stressful conditions and
allows to differentiate experienced and novice operators during their
performance on a simulator. If the CS-index proves to be reliable enough, its
combination with the Automated Expert Modeling for Automated Student Evaluation
(AEMASE) approach can considerably raise the efficiency of operator training. Keywords: heart rate variability; cognitive workload; training | |||
| Tunnel Operator Training with a Conversational Agent-Assistant | | BIBAK | Full-Text | 575-584 | |
| Eric Buiël; Jan Lubbers; Willem A. van Doesburg; Tijmen Muller | |||
| A tunnel operator monitors and regulates the flow of traffic inside a
tunnel. Tunnel operators need to train in a simulator regularly in order to
maintain proficiency in handling incident situations. During quiet working
hours, the operator has enough time for training. But generally at that time no
instructor or colleague operators are present to provide instruction, advises,
and feedback. As a solution, we have designed an automated training system. The
system employs a conversational agent which supports the operator's situation
assessment tasks. The agent exhibits peer behavior which is unobtrusively
directed by didactic strategies. In this paper we present the design,
development and application of the agent. Keywords: Agent-Based Modeling and Training; Cognitive Modeling; Constructive
Learning; Intelligent Virtual Agent | |||
| Evaluating Training with Cognitive State Sensing Technology | | BIBA | Full-Text | 585-594 | |
| Patrick L. Craven; Patrice D. Tremoulet; Joyce Barton; Steven J. Tourville; Yaela Dahan-Marks | |||
| Five different training techniques (classroom, video, game-based, computer-based, and simulator) were compared using neurophysiological measurements. The best performance was displayed by individuals in the classroom and video conditions. These participants also displayed the lowest levels of cognitive workload and the highest levels of engagement. The poorest performance on the training was exhibited by individuals in the computer-based and game conditions. These participants also displayed the highest levels of cognitive workload, the lowest levels of engagement, and computer-based had the highest levels of drowsiness. As expected, the testing phases of the training had the highest levels of workload. In general, engagement dropped and distraction increased during the training phase when the material was first presented to participants. However, participants who could keep engagement high during this period performed better. This suggests that mental state monitoring during training could help provide a mechanism for alleviating distraction and inattention and boost training efficacy. | |||
| Identifying the Nature of Knowledge Using the Pressures Applied to a Computer Mouse | | BIBAK | Full-Text | 595-600 | |
| Martha E. Crosby; Curtis S. Ikehara; Wendy S. Ark | |||
| The nature of knowledge retention is not that a student either knows or
doesn't. Using signal detection theory, the correct and incorrect responses a
student provides can each be subdivided into two more levels of knowledge using
the student's confidence of answer correctness. The proposed study will attempt
to link confidence of answer correctness to the categorized pressures applied
to a computer mouse allowing for the partitioning of responses. Twenty
participants that were part of a pedagogical methods study will be retested
using a computer-based multiple choice test and pressure sensitive computer
mouse. Participants will also rate their confidence of answer correctness. It
is hypothesized that the analyzed pressures applied to the computer mouse will
indicate the confidence of answer correctness. Using the categorized pressures
from the computer mouse allows for the real-time assessment of a student's
knowledge to guide pedagogical follow-up. Keywords: knowledge; pressure sensitive computer mouse; confidence of correctness | |||
| Realizing Adaptive Instruction (Ad-In): The Convergence of Learning, Instruction, and Assessment | | BIBAK | Full-Text | 601-610 | |
| Edward Dieterle; John Murray | |||
| In this paper, we define adaptive instruction, or Ad-In, as applied to
sophisticated skills development systems that target learning and assessment in
a highly individualized and interactive manner. We argue that the successful
design and use of such systems rely heavily upon the interrelationships among
learning styles, instructional theories, and assessment methods, in the context
of personalized learning. We outline and structure the links among these topics
by drawing upon recent empirical studies of virtual environments and augmented
realities. The paper also presents a candidate architecture for applying Ad-In
concepts in an intelligent interactive environment for skills development. Keywords: Adaptive instruction; augmented reality; immersion; intelligent tutoring
assistant; multi-user virtual environment; neomillennial learning styles | |||
| Adaptive Learning via Social Cognitive Theory and Digital Cultural Ecosystems | | BIBA | Full-Text | 611-619 | |
| Joseph Juhnke; Adam R. Kallish | |||
| This paper will look at the human predisposition to oral tradition and its effectiveness as a learning tool to convey mission-critical information. After exploring the effectiveness of the conveyance of information, the paper will examine current adaptive learning research and develop a system that will marry the strengths of oral tradition with those of an optimal adaptive learning environment. Emphasis will be made in the area of military service personnel stationed in contested cultures, the aiding of their arrival and once established their continual improvement processes. This paper will then illustrate a digital cultural ecosystem that leverages the strengths of current industry thinking in digital community development and social architecture combining the adaptive learning models discussed earlier to create a dynamic digital social ecology that could significantly improve the transition process by exposing service personnel to the collective learning of all of the personnel currently and previously deployed to a particular region. It will illustrate tools and techniques that can be used to filter the quality of the collective intelligence, the dynamic categorization of new narrative and the selective recommendation of content as an adaptive learning technique. This system will incorporate a virtual environment to test the quality of learning before the military personnel are deployed and a capture and debrief system that will enable the continual improvement of service personnel as they complete missions during their deployment. | |||
| The Interaction between Chinese University Students' Computer Use and Their Attitudes toward Computer in Learning and Innovation | | BIBAK | Full-Text | 620-629 | |
| Ye Liu; Xiaolan Fu | |||
| A survey study investigated the dynamic interaction between Chinese
university students' computer use and their attitudes toward computer in
learning and innovation. The relationships among attitudes toward computer in
learning (ACL), attitudes toward innovation (ATI), and self-perception on
computer skill (SPCS), were also examined. Participants were 292 university
students from three universities in Beijing, and all of them had used computer
and Internet before. The results showed that: (a) Previous computer use could
predict recent computer use with ACL, ATI, and SPCS as mediate variables; (b)
males were more confident than females in SPCS, but there was no gender
difference in either ACL or ATI; and (c) the participants' notion of innovation
was significantly more positive than their innovative action. Keywords: Computer use; Computer attitude; Attitudes toward innovation;
Self-perception on computer skill; Gender difference | |||
| Peak Performance Trainer (PPT™): Interactive Neuro-educational Technology to Increase the Pace and Efficiency of Rifle Marksmanship Training | | BIBAK | Full-Text | 630-639 | |
| Giby Raphael; Chris Berka; Djordje Popovic; Gregory K. W. K. Chung; Sam O. Nagashima; Adrienne Behneman; Gene Davis; Robin Johnson | |||
| Marksmanship training involves a combination of classroom instructional
learning and field practice involving the instantiation of a well-defined set
of sensory, motor and cognitive skills. Current training procedures rely
heavily on conventional classroom instruction often with qualitative assessment
based on observation (i.e. coaching). We have developed a novel device called
the Peak Performance Trainer (PPT™) which can accelerate the progression
from novice-to-expert based on automated inferences from neurophysiological
measurements. Our previous work has revealed specific EEG correlates to stages
of skill acquisition in simple learning and memory tasks. We have incorporated
this knowledge as well as an array of other physiological metrics to develop a
field-deployable training technology with continuous physiological monitoring
in combination with simultaneous measures of performance, workload, engagement
and distraction, accuracy, speed and efficiency. This paper outlines the
features of the PPT and the preliminary results of its use in marksmanship
training. Keywords: EEG; Heart rate; Alpha; Theta; Haptics | |||
| The Quality of Training Effectiveness Assessment (QTEA) Tool Applied to the Naval Aviation Training Context | | BIBAK | Full-Text | 640-649 | |
| Tom Schnell; Rich Cornwall; Melissa Walwanis; Jeff Grubb | |||
| Today, flight trainers use objective measures of task performance and
additional estimated, subjective data to assess the cognitive workload and
situation awareness of trainees. This data is very useful in training
assessment but trainees can succeed at performing a task purely by accident
(referred to as "miserable success"). Additionally the trainee can be in a less
than optimal for learning cognitive state when the instructor operator applies
brute force training tasks and methods with little regard to the learning curve
which can result in the training being too easy or, more often, too difficult,
thereby inducing negative learning. In order to provide the instructor with
additional quantitative data on student performance, we have designed the
Quality of Training Effectiveness Assessment (QTEA) concept. QTEA is conceived
as a system that allows the trainer to assess a student in real-time using
sensors that can quantify the cognitive and physiological workload. Keywords: Neurocognitive measures; operator state characterization; flight training | |||
| Perceptually-Informed Virtual Environment (PerceiVE) Design Tool | | BIBAK | Full-Text | 650-657 | |
| Anna Skinner; Jack Maxwell Vice; Corinna E. Lathan; Cali M. Fidopiastis; Chris Berka; Marc M. Sebrechts | |||
| Virtual environments (VE's) are becoming more and more prevalent as training
tools for both military and civilian applications. The common assumption is
that the more realistic the VE, the better the transfer of training to real
world tasks. However, some aspects of task content and fidelity may result in
stronger transfer of training than even the most high fidelity simulations.
This research effort seeks to demonstrate the technical feasibility of a
Perceptually-informed Virtual Environment (PerceiVE) Design Tool, capable of
dynamically detecting changes in operator behavior and physiology throughout a
VE experience and comparing those changes to operator behavior and physiology
in real-world tasks. This approach could potentially determine which aspects of
VE fidelity will have the highest impact on transfer of training. A preliminary
study was conducted in which psychophysiological and performance data were
compared for a visual search tasks with low and high fidelity conditions. While
no significant performance effects were found across conditions, event-related
potential (ERP) data revealed significant differences between the low and high
fidelity stimulus conditions. These results suggest that psychophysiological
measures may provide a more sensitive and objective measure for determining VE
fidelity requirements. Keywords: Psychophysiological Measures; Virtual Environments; Fidelity; Transfer of
Training; Simulation Design | |||
| Can Neurophysiologic Synchronies Provide a Platform for Adapting Team Performance? | | BIBAK | Full-Text | 658-667 | |
| Ronald H. Stevens; Trysha Galloway; Chris Berka; Marcia Sprang | |||
| We have explored using neurophysiologic patterns as an approach for
developing a deeper understanding of how teams collaborate when solving
time-critical, complex real-world problems. Fifteen students solved substance
abuse management simulations individually, and then in teams of three while
measures of mental workload (WL) and engagement (E) were generated by
electroencephalography (EEG). High and low workload and engagement levels were
identified at each epoch for each team member and vectors of these measures
were clustered by self organizing artificial neural networks. The resulting
patterns, termed neurophysiologic synchronies, differed for the five teams
reflecting the teams' efficiency. When the neural synchronies were compared
across the collaboration, segments were identified where different synchronies
were preferentially expressed. This approach may provide an approach for
monitoring the quality of team work during complex, real-world and possible one
of a kind problem solving, and for adaptively modifying the teamwork flow when
optimal synchronies are not frequent. Keywords: Collaboration; EEG; Neurophysiologic synchrony | |||
| Seeing the World through an Expert's Eyes: Context-Aware Display as a Training Companion | | BIBA | Full-Text | 668-677 | |
| Marc T. Tomlinson; Michael Howe; Bradley C. Love | |||
| Responsive Adaptive Display Anticipates Requests (RADAR) is a domain general system that learns to highlight an individual's preferred information displays, given the current context. Previous studies with human subjects in a video game environment demonstrate that RADAR is an effective cognitive aid. RADAR increases situation awareness and reduces cognitive load by anticipating and providing task relevant information. Additionally, because RADAR's fit to a user's behavior encapsulates the user's situation-driven information preferences, RADAR also excels as a descriptive and predictive assessment tool. Here, we focus RADAR as a training aid. We test the hypothesis that novices can benefit from training under a RADAR model derived from an expert's behavioral patterns. The results indicate that novices exposed to an expert's information preferences through RADAR rapidly learn to conform to the expert's preferences. | |||
| Translating Learning Theories into Physiological Hypotheses | | BIBAK | Full-Text | 678-686 | |
| Jennifer J. Vogel-Walcutt; Denise M. Nicholson; Clint A. Bowers | |||
| The battlefield has become an increasingly more complicated setting in which
to operate. Additional stressors, complexity, and novel situations have
challenged not only those in the field, but consequently also those in
training. More information must be imparted to the trainees, yet more time is
not available. Thus, in this paper, we consider one way to optimize the
delivery and acquisition of knowledge that can be meaningfully applied to the
field setting. We hypothesize that for learning efficiency to be maximized, we
need to keep learners in a constant state of engagement and absorption. As
such, we consider neuro-physiological hypotheses that can help prescribe
mitigation strategies to reduce the impact of sub-optimal learning. Keywords: Learning efficiency; Augmented cognition; Adaptive training | |||
| Adapting Instruction | | BIBA | Full-Text | 687-695 | |
| Wallace H. Wulfeck | |||
| It is often claimed that adapting instruction to an individual's progress, personal characteristics or preferences will somehow increase learning, and there have been literally thousands of studies over at least the past 100 years exploring this idea. This presentation will review various approaches to adapting instruction, such as changing the rate, difficulty, sequence or structure, instructional strategy or instructional media on the basis of learner progress, prior knowledge, aptitudes or preferences, under various forms of instructor, learner, program, or opponent control. This paper gives an organizing framework, describes some of the theoretical underpinnings for particular adaptations, and describes experimental and practical criteria for evaluating claims of efficacy and efficiency of instructional adaptations. | |||
| Assessment of Cognitive Neural Correlates for a Functional Near Infrared-Based Brain Computer Interface System | | BIBAK | Full-Text | 699-708 | |
| Hasan Ayaz; Patricia A. Shewokis; Scott C. Bunce; Maria T. Schultheis; Banu Onaral | |||
| Functional Near Infrared Spectroscopy (fNIR) is a promising brain imaging
technology that relies on optical techniques to detect changes of hemodynamic
responses within the prefrontal cortex in response to sensory, motor, or
cognitive activation. fNIR is safe, non-invasive, affordable, and highly
portable. The objective of this study is to determine if biomarkers of neural
activity generated by intentional cognitive activity, as measured by fNIR, can
be used to communicate directly from the brain to a computer. A
bar-size-control task based on a closed-loop system was designed and tested
with 5 healthy subjects across two days. Comparisons of the average task and
rest period oxygenation changes are significantly different (p<0.01). The
average task completion time (reaching +90%) decreases with practice: day1
(mean 52.3 sec) and day2 (mean 39.1 sec). These preliminary results suggest
that a closed-loop fNIR-based BCI can allow for a human-computer interaction
with a mind switch task. Keywords: Brain Computer Interface; fNIR; Near Infrared Spectroscopy | |||
| Systems and Strategies for Accessing the Information Content of fNIRS Imaging in Support of Noninvasive BCI Applications | | BIBAK | Full-Text | 709-718 | |
| Randall L. Barbour; Harry L. Graber; Yong Xu; Yaling Pei; Glenn R. Wylie; Gerald T. Voelbel; John DeLuca; Andrei V. Medvedev | |||
| An essential component for a practical noninvasive brain-computer interface
(BCI) system is data recording technology that can access the
information-processing activity of the brain with high fidelity and throughput.
Functional near-infrared spectroscopic (fNIRS) imaging is a methodology that
shows promise in meeting this need, having a demonstrated sensitivity to both
the slow hemodynamic response that follows neuroactivation and to the lower
amplitude fast optical response that is considered a direct correlate of
neuroactivation. In this report we summarize the technology integration
strategy we have developed that permits detection of both signal types with a
single measuring platform, and present results that document the ability to
detect these data types transcranially in response to two different visual
paradigms. Also emphasized is the effectiveness of different data analysis
approaches that serve to isolate signals of interest. The findings support the
practical utility of NIRS-based imaging methods for development of BCI
applications. Keywords: Diffuse Optical Tomography; fNIRS imaging; fast signal; combinatorial Hb
States; Neuroactivation; Visual Stimulus; NIRS Technology | |||
| Brain-Computer Interaction | | BIBAK | Full-Text | 719-723 | |
| Peter Brunner; Gerwin Schalk | |||
| Detection and automated interpretation of attention-related or
intention-related brain activity carries significant promise for many military
and civilian applications. This interpretation of brain activity could provide
information about a person's intended movements, imagined movements, or
attentional focus, and thus could be valuable for optimizing or replacing
traditional motor-based communication between a person and a computer or other
output devices. We describe here the objective and preliminary results of our
studies in this area. Keywords: Brain-computer interface; BCI; Neural Engineering; Neural Prosthesis | |||
| P300 Based Brain Computer Interfaces: A Progress Report | | BIBAK | Full-Text | 724-731 | |
| Emanuel Donchin; Yael Arbel | |||
| Brain-Computer Interfaces (BCI) are the only means of communication
available to patients who are locked-in, that is for patients who are
completely paralyzed yet are fully conscious. We focus on the status of the
P300-BCI first described by Farwell and Donchin (1988). This system has now
been tested with several dozen ALS patients and some have been using this
approach for communication at a very extensive level. More recently, we have
adapted this BCI (in collaboration with the laboratory of Dr. Rajiv Dubey) to
the control of a robotic arm. In this presentation we will discuss the special
problems of human computer interaction that occur within the context of such a
BCI. The special needs of the users forced the development of variants of this
system, each with advantages and disadvantages. The general principles that can
be derived from the experience we have had with this BCI will be reviewed. Keywords: Brain Computer Interface (BCI); P300; wheelchair-mounted robotic arm (WMRA) | |||
| Goal-Oriented Control with Brain-Computer Interface | | BIBAK | Full-Text | 732-740 | |
| Günter Edlinger; Clemens Holzner; Christoph Groenegress; Christoph Guger; Mel Slater | |||
| A brain-computer interface (BCI) is a new communication channel between the
human brain and a digital computer. Such systems have been designed to support
disabled people for communication and environmental control. In more recent
research also BCI control in combination with Virtual Environments (VE) gains
more and more interest. Within this study we present experiments combining BCI
systems and VE for navigation and control purposes just by thoughts. Results
show that the new P300 based BCI system allows a very reliable control of the
VR system. Of special importance is the possibility to select very rapidly the
specific command out of many different choices. The study suggests that more
than 80% of the population could use such a BCI within 5 minutes of training
only. This eliminates the usage of decision trees as previously done with BCI
systems. Keywords: Brain-computer interface; virtual reality; P300 evoked potential | |||
| Wearable and Wireless Brain-Computer Interface and Its Applications | | BIBAK | Full-Text | 741-748 | |
| Chin-Teng Lin; Li-Wei Ko; Che-Jui Chang; Yu-Te Wang; Chia-Hsin Chung; Fu-Shu Yang; Jeng-Ren Duann; Tzyy-Ping Jung; Jin-Chern Chiou | |||
| This study extends our previous work on mobile & wireless EEG
acquisition to a truly wearable and wireless human-machine interface, NCTU
Brain-Computer-Interface-headband (BCI-headband), featuring: (1) dry
Micro-Electro-Mechanical System (MEMS) EEG electrodes with 400 ganged contacts
for acquiring signals from non-hairy sites without use of gel or skin
preparation; (2) a miniature data acquisition circuitry; (3) wireless
telemetry; and (4) online signal processing on a commercially available cell
phone or a lightweight, wearable digital signal processing module. The
applicability of the NCTU BCI-headband to EEG monitoring in real-world
environments was demonstrated in a sample study: cognitive-state monitoring and
management of participants performing normal tasks. Keywords: Dry electrodes; brain computer interface; mobile and wireless EEG | |||
| Mind Monitoring via Mobile Brain-Body Imaging | | BIBAK | Full-Text | 749-758 | |
| Scott Makeig | |||
| Current brain-computer interface (BCI) research attempts to estimate
intended operator body or cursor movements from his/her electroencephalographic
(EEG) activity alone. More general methods of monitoring operator cognitive
state, intentions, motivations, and reactions to events might be based on
continuous monitoring of the operator's (EEG) as well as his of her body and
eye movements and, to the extent possible, her or his multisensory input. Joint
modeling of this data should attempt to identify individualized modes of
brain/body activity and/or reactivity that appear in the operator's brain
and/or behavior in distinct cognitive contexts, if successful producing, in
effect, a new mobile brain/body imaging (MoBI) modality. Robust MoBI could
allow development of new brain/body-system interface (BBI) designs performing
multidimensional monitoring of an operator's changing cognitive state including
their movement intentions and motivations and ('top-down') apprehension of
sensory events. Keywords: cognitive monitoring; electroencephalography (EEG); motion capture;
independent component analysis (ICA); brain-computer interface (BCI); mobile
brain/body imaging (MoBI); human-computer interface (HCI) | |||
| Utilizing Secondary Input from Passive Brain-Computer Interfaces for Enhancing Human-Machine Interaction | | BIBA | Full-Text | 759-771 | |
| Thorsten O. Zander; Christian Kothe; S. Welke; Matthias Roetting | |||
| A Brain-Computer Interface (BCI) directly translates patterns of brain activity to input for controlling a machine. The introduction of methods from statistical machine learning [1] to the field of brain-computer interfacing (BCI) had a deep impact on classification accuracy. It also minimized the effort needed to build up the skill of controlling a BCI system [2]. This enabled other fields of research to adapt methods from BCI research for their own purposes [3, 4]. Team PhyPA, the research group for physiological parameters of the chair for Human-Machine Systems (HMS) of the Technical University of Berlin, focuses on enabling new communication channels for HMS. Especially the use of passive BCIs (pBCI) [3, 4], not dependent on any intended action of the user, show a high potential for enhancing the interaction in HMS [5]. Additionally, as actual classification rates are still below the threshold for efficient primary control [6, 7] in HMS, we focus on establishing a secondary, BCI-based communication channel. This kind of interaction does not necessarily disturb the primary mode of interaction, providing a low usage cost and hence an efficient way of enhancement. We have designed several applications following this approach. Here we are going to present briefly the results from two studies, which show the capabilities arising from the use of passive and secondary BCI interaction. First, we show that a pBCI can be utilized to gain valuable information about HMSs, which are hard to detect by exogeneous factors. By mimicking a typical BCI interaction, we have been able to identify and isolate a factor inducing non-stationarities with a deep impact on the feature dynamics. The retained information can be utilized for automatically triggered classifier adaptation. And second, we show that pBCIs are indeed capable to enhance common HMS interaction outside the laboratory. With this, we would like to feed back our experiences made with the use of BCIs for HMS. We hope to provide new and useful information about brain dynamics which might be helpful for ongoing research in augmented cognition. | |||
| Augmented Cognition as Rehabilitation: Facilitating Neuroplasticity? | | BIBAK | Full-Text | 775-781 | |
| Michael Feuerstein; Gina Luff; Mark Peugeot; Miki Moskowitz; Briana Todd | |||
| Different types of brain injury are associated with deficits in working
memory, executive functioning, and information processing speed, which can
impact performance at work. Augmented Cognition (AugCog), a technology
developed to improve human performance in complex tasks, may have potential for
optimizing cognitive functioning in the context of work for those with mild to
moderate cognitive deficits. AugCog is a way to accommodate or augment function
thus improving the performance of the operator. This approach may facilitate
neuroplasticity that can occur following injury to the brain. The authors will
provide the rationale, operational structure, and potential application to
occupational rehabilitation. Keywords: Augmented cognition; occupational rehabilitation; cognitive limitations;
mild brain injury | |||
| Embodying Meaning in Bio-cognitive Aid Design | | BIBA | Full-Text | 782-791 | |
| Daniel Garrison; Victoria Garrison | |||
| Through analysis involving components of theory, concept, and semantics, we synthesize a set of insights and relations existing through embodiment that have applicability to the design of cognitive aids. Of note, we explore the areas of embodied interaction, embodied user interfaces, and embodied cognition. Additionally, we demonstrate how meaning is created and distributed in and through the areas. We then apply findings to the development of an embodied user interface developed to cognitively aid in renovation projects. | |||
| CI Therapy: A Method for Harnessing Neuroplastic Changes to Improve Rehabilitation after Damage to the Brain | | BIBA | Full-Text | 792-799 | |
| L. V. Gauthier; E. Taub | |||
| Constraint-Induced Movement (CI) therapy has been successfully implemented for treating motor deficit resulting from a variety of previously intractable neurological conditions such as traumatic brain injury. CI therapy's efficacy can be attributed to two interrelated mechanisms: overcoming "learned nonuse" and neuroplasticity. Voxel-based morphometry (VBM) analyses have demonstrated that CI therapy produces lasting structural changes to the human brain. Patients that received full CI therapy demonstrated profuse grey matter increases in sensory and motor areas and hippocampus, whereas those who received only intensive motor practice did not. The magnitude of the observed structural changes was correlated with the extent to which the patient regained use of the impaired arm for daily activities. These findings demonstrate that the two mechanisms believed to underlie improvement from CI therapy, overcoming "learned nonuse" and neuroplasticity, act synergistically. Therefore, a bidirectional approach to treating brain injury, one that targets both brain and behavior, is suggested. | |||
| Augmented Cognition Design Approaches for Treating Mild Traumatic Brain Injuries | | BIBAK | Full-Text | 800-809 | |
| Kay M. Stanney; Kelly S. Hale; David Jones | |||
| Augmented cognition could serve as an innovative rehabilitation approach for
mild traumatic brain injuries, where issues with cognition, behavior, and
affective responses are monitored in real-time and mitigation strategies are
triggered to resolve performance or behavior issues. Such mitigations could
guide individuals in addressing the current situation (e.g., performance
decrement, undesired behavior, negative affective response), as well as provide
rehabilitation support to improve performance and behavior in subsequent
situations. This paper focuses on mitigation strategies that are suitable for
an augmented cognition rehabilitation setting, with the goal of supporting
recovery from suboptimal performance and providing rehabilitation tools in
real-time, operational context. Keywords: Augmented cognition; mild traumatic brain injury; mitigation strategies | |||
| Brain Processes and Neurofeedback for Performance Enhancement of Precision Motor Behavior | | BIBAK | Full-Text | 810-817 | |
| B. Hatfield; A. Haufler; José L. Contreras-Vidal | |||
| Based on a number of empirical investigations of cerebral cortical dynamics
during precision aiming tasks (i.e. marksmanship) employing
electroencephalography (EEG) refinement of cortical activity and attenuation of
nonessential cortico-cortical communication with the motor planning regions of
the brain results in superior performance. Employment of EEG neurofeedback
during the aiming period of target shooting designed to reduce cortical
activation resulted in improved performance in skilled marksmen. Such an effect
implies that refinement of cortical activity is causally related to
performance. Recently, we examined cerebral cortical dynamics during the stress
of competitive target shooting and observed increased activation and
cortico-cortical communication between non-motor and motor regions relative to
a practice-alone condition. As predicted, this finding was associated with
degradation of shooting performance. These findings imply that neurofeedback
targeted to brain regions related to emotional responding may preserve the
cortical dynamics associated with superior performance resulting in improved
accuracy of precision aiming performance. Keywords: electroencephalography (EEG); psychomotor performance; cognitive
neuroscience; stress; kinematics | |||
| Long Term Repair of Learning Disability through Short-Term Reduction of CNS Inhibition | | BIBAK | Full-Text | 818-825 | |
| H. Craig Heller; Damien Colas; Norman F. Ruby; Fabian Fernandez; Bayarasaikhan Chuluun; Martina Blank; Craig C. Garner | |||
| Learning disabilities are serious societal problems contributing to a loss
of quality of life for affected individuals and their families. We hypothesized
that the learning disability in Down Syndrome and perhaps in other
neurodegenerative disorders is due to an imbalance between inhibitory and
excitatory tone in the CNS. Specifically, we predicted that reduction of GABA
related inhibition would improve learning. We used the TsDn65 mouse model of
Down Syndrome and treated adult mice with daily doses of different GABA
antagonists. Following treatments learning performance of these mice in several
rodent learning tasks was indistinguishable from the performance of wild type
mice, and the learning improvement lasted for months after the treatment ended.
We are now exploring the mechanism of this durable neuroplastic effect and
asking whether it would generalize to other learning disorders or optimize
learning in wild type mice. Keywords: GABA; picrotoxin; pentylenetetrazole; bilobilide; flumazinil; Down Syndrome;
TsDn65 mice; novel object recognition | |||
| Development of Sensitive, Specific, and Deployable Methods for Detecting and Discriminating mTBI and PTSD | | BIBAK | Full-Text | 826-835 | |
| Robin R. Johnson; Djordje Popovic; Deborah Perlick; Dennis Dyck; Chris Berka | |||
| This paper presents a theoretical framework for the development of
non-invasive methods for detection and discrimination between mild traumatic
brain injury (mTBI) and post-traumatic stress disorder (PTSD). Growing use of
IEDs and increased pace of multiple deployment cycles in current conflicts has
lead to significant increases in exposure to risks for these conditions.
Co-morbidity of these conditions is common, diagnostically challenging, and
controversial. Development of easy to use, deployable diagnostic tools would
allow for accurate early identification and intervention. Early intervention
increases the potential for positive outcomes for both the individual and their
families. In addition, the appropriately designed system could be used
epidemiologically to screen returning soldiers for these conditions that may
otherwise not be appropriately assessed until much later, if at all. The
framework presented here proposes that a wireless, portable EEG/EKG based
device may be an appropriate platform upon which to develop such an assessment
tool. Keywords: Electroencephalogram (EEG); Electrocardiogram (EKG); Post-Traumatic Stress
Disorder (PTSD); mild Traumatic Brain Injury (mTBI) | |||
| Physiologically Driven Rehabilitation Using Virtual Reality | | BIBAK | Full-Text | 836-845 | |
| Angela M. Salva; Antonio J. Alban; Mark D. Wiederhold; Brenda K. Wiederhold; Lingjun Kong | |||
| Creating a platform that allows the fusion of real-time physiological
measurements and virtual reality (VR) simulation will greatly improve present
human-computer interaction, adaptive displays, military training, and anxiety
therapy. The Virtual Reality Medical Center (VRMC) has developed a
physiologically-driven rehabilitation platform that correctly assesses user
anxiety levels based on multiple real time physiological measures, determines
the optimal level of physiological arousal for each individual user, and
automates the virtual simulation to the proper intensity for each user.
Additionally, VRMC collaborates with UCF to develop novel, state-of-the-art
sensors to be integrated within the platform that are capable of measuring
electrocardiogram, (EEG), skin conductance, gait, and pupillometry. In Phase I
VRMC developed a capability to monitor, fuse, and evaluate physiological
measures (heart rate, skin conductance, skin temperature, and respiration) in
real time to assess user anxiety levels. The physiological data collected will
be used to assess user anxiety levels in real time as neutral, low, or high
with 90% accuracy and to determine the optimal level of physiological arousal
for each individual user. Keywords: physiological measurement; stroke; traumatic brain injury; cerebrovascular
accident; rehabilitation; cognitive rehabilitation; simulation; mixed reality | |||