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FAC Tables of Contents: 070911131415

FAC 2015: 9th International Conference on Foundations of Augmented Cognition

Fullname:AC 2015: 9th International Conference on Foundations of Augmented Cognition: Advancing Human Performance and Decision-Making through Adaptive Systems
Note:Volume 15 of HCI International 2015
Editors:Dylan D. Schmorrow; Cali M. Fidopiastis
Location:Los Angeles, California
Dates:2015-Aug-02 to 2015-Aug-07
Publisher:Springer International Publishing
Series:Lecture Notes in Computer Science 9183
Standard No:DOI: 10.1007/978-3-319-20816-9 hcibib: FAC15; ISBN: 978-3-319-20815-2 (print), 978-3-319-20816-9 (online)
Papers:79
Pages:837
Links:Online Proceedings | Conference Website
  1. Cognitive Performance and Workload
  2. BCI and Operational Neuroscience
  3. Cognition, Perception and Emotion Measurement
  4. Adaptive Tutoring and Training
  5. Applications of Augmented Cognition

Cognitive Performance and Workload

Error Visualization and Information-Seeking Behavior for Air-Vehicle Control BIBAFull-Text 3-11
  Lewis L. Chuang
A control schema for a human-machine system allows the human operator to be integrated as a mathematical description in a closed-loop control system, i.e., a pilot in an aircraft. Such an approach typically assumes that error feedback is perfectly communicated to the pilot who is responsible for tracking a single flight variable. However, this is unlikely to be true in a flight simulator or a real flight environment. This paper discusses different aspects that pertain to error visualization and the pilot's ability in seeking out relevant information across a range of flight variables.
DataShopping for Performance Predictions BIBAKFull-Text 12-23
  Michael Collins; Kevin A. Gluck; Tiffany S. Jastrzembski
Mathematical models of learning have been created to capitalize on the regularities that are seen when individuals acquire new skills, which could be useful if implemented in learning management systems. One such mathematical model is the Predictive Performance Equation (PPE). It is the intent that PPE will be used to predict the performance of individuals to inform real-world education and training decisions. However, in order to improve mathematical models of learning, data from multiple samples are needed. Online data repositories, such as Carnegie Mellon University's DataShop, provide data from multiple studies at fine levels of granularity. In this paper, we describe results from a set of analyses ranging across levels of granularity in order to assess the predictive validity of PPE in educational contexts available in the repository.
Keywords: Performance prediction; Datashop; Repository; Learning optimization; Mathematical models
Using Context to Optimize a Functional State Estimation Engine in Unmanned Aircraft System Operations BIBAKFull-Text 24-35
  Kevin Durkee; Scott Pappada; Andres Ortiz; John Feeney; Scott Galster
As UAS operations continue to expand, the ability to monitor real-time cognitive states of human operators would be a valuable asset. Although great strides have been made toward this capability using physiological signals, the inherent noisiness of these data hinders its readiness for operational deployment. We theorize the addition of contextual data alongside physiological signals could improve the accuracy of cognitive state classifiers. In this paper, we review a cognitive workload model development effort conducted in a simulated UAS task environment at the Air Force Research Laboratory (AFRL). Real-time workload model classifiers were trained using three levels of physiological data inputs both with and without context added. Following the evaluation of each classifier using four model evaluation metrics, we conclude that by adding contextual data to physiological-based models, we improved the ability to reliably measure real-time cognitive workload in our UAS operations test case.
Keywords: Context; Human performance; Modeling and simulation; Physiological measurement; Workload; UAS
Methods for Determining the Role of Fatigue and Cognitive Load on Behavior Detection Officers (BDOs) Performance in the Field BIBAKFull-Text 36-43
  Robert Kittinger; James Bender
Job analysis and cognitive task analysis (CTA) are two methods for identifying all job tasks, both observable and unobservable respectively, which correlate to successful job performance. These methods will be applied to the Transportation Security Administration's (TSA's) Behavior Detection Officers (BDOs) to identify the elements which compose their job and to identify what elements are most difficult, important and frequently accomplished in the support of our national security. This paper will describe one method for conducting a job analysis on the BDO job and then a method for following that work with a cognitive task analysis. The described JA and CTA will provide a scientific foundation for future research and analysis of the BDO job position and successful performance of that job.
Keywords: National security; Homeland security; Transportation security administration; TSA; Behavior detection officers; BDO; Job analysis; Work analysis; Cognitive task analysis; Cognitive load; Cognitive fatigue; Fatigue; Job performance; Methodology
Workload Is Multidimensional, Not Unitary: What Now? BIBAKFull-Text 44-55
  Gerald Matthews; Lauren Reinerman-Jones; Ryan Wohleber; Jinchao Lin; Joe Mercado; Julian, IV Abich
It is commonly assumed that workload is a unitary construct, but recent data suggest that there are multiple subjective and objective facets of workload that are only weakly intercorrelated. This article reviews the implications of treating workload as multivariate. Examples from several simulated task environments show that high subjective workload is compatible with a variety of patterns of multivariate psychophysiological response. Better understanding of the cognitive neuroscience of the different components of workload, including stress components, is required. At a practical level, neither subjective workload measures nor single physiological responses are adequate for evaluating task demands, building predictive models of human performance, and driving augmented cognition applications. Multivariate algorithms that accommodate the variability of cognitive and affective responses to demanding tasks are needed.
Keywords: Workload; Task demands; Psychophysiology; Electroencephalogram (EEG); Electrocardiogram (ECG); Stress; Performance; Individual differences
Time Dependent Effects of Transcranial Direct Current Stimulation and Caffeine on Vigilance Performance During Extended Wakefulness BIBAKFull-Text 56-62
  R. Andy McKinley; Lindsey K. McIntire; Ryan Schilling; Chuck Goodyear; Justin Nelson
Background: Previously, we found that transcranial direct current stimulation (tDCS) preserved vigilance performance approximately twice as well and three times as long as caffeine during a period of extended wakefulness. Vigilance performance often declines linearly over the period of watch, but in our previous study the performance trends over the period of watch were not analyzed. Hence, it was not known whether the intervention applied reduced the vigilance decrement, or simply shifted the performance to a higher mean value while maintaining a similar slope.
   Objective: Our objective was to evaluate the time-dependent effects (within each period of watch) of anodal transcranial direct current stimulation (tDCS) applied to the pre-frontal cortex at 2 mA for 30 min. We then compared these results to those of caffeine as well as the effects of both interventions on arousal.
   Methods: The period of watch was segregated into equal time segments and target identification accuracy was averaged across subjects in each group. These values were used in an analysis of covariance (separately for each session) as the dependent variable. Factors were group and subject nested in group.
   Results: The results indicated there is not a significant difference in slope (i.e. vigilance decrement) between the treatment conditions (tDCS, caffeine, and sham) within each period of watch. However, as reported previously, there was a significant difference in mean change from baseline between the treatment conditions.
   Conclusion: Our data suggests that tDCS does not prevent the vigilance decrement within the period of watch. Rather, it shifts performance to higher mean values by a scalar multiple while maintaining a similar slope.
Keywords: Transcranial direct current stimulation; Sleep deprivation; Caffeine; Cognition; Vigilance
Towards a Translational Method for Studying the Influence of Motivational and Affective Variables on Performance During Human-Computer Interactions BIBAKFull-Text 63-72
  Jason S. Metcalfe; Stephen M. Gordon; Antony D. Passaro; Bret Kellihan; Kelvin S. Oie
A primary goal in operational neuroscience is to create translational pathways linking laboratory observations with real-world applications. Achieving this requires a method that enables study of variability in operator performance that does not typically emerge under controlled laboratory circumstances; the present paper describes the development of such a paradigm. An essential aspect of the design process involved eliciting subject engagement without using extrinsic incentive (e.g. money) as a motivating stressor and, instead, tapping an appropriate intrinsic incentive (i.e. competitive stress). Two sources of competition were initially considered including one based on self-competition and another based on competition with another individual; ultimately, the latter approach was selected. A virtual competitor was designed to affect individual valuation of momentary successes and failures in specific ways and preliminary results revealed early indicators of success in meeting this goal. Discussion focuses on implications and challenges for future research using similar translational paradigms.
Keywords: Competitive stress; Affect; Motivation; Translational science
Impact of Acute Stress on Attentional Orienting to Social Cues in Special Operations Personnel BIBAKFull-Text 73-81
  Charles A. Morgan; Harlan M. Fichtenholtz; Bartlett Russell
The goal of the present study was to characterize the effects of an acutely stressful situation on attentional orienting to social cues. Participants were tested before and during a highly stressful military training course. During the task, participants shown faces at fixation that concurrently displayed dynamic gaze shifts and expression changes from neutral to fearful or happy emotions. Military-relevant targets subsequently appeared in the periphery and were spatially congruent or incongruent with the gaze direction. Participants showed faster responses during fearful face trials during the high stress condition compared to baseline, while the response on happy face trials did not change. Additionally, enhanced performance was related to self-report reappraisal use during emotion regulation at baseline. Reaction times to threatening targets were faster on validly cued trials during both tests. Trials with safe targets showed no differences at baseline. These results suggest that acute stress plays a role in how individuals respond in the presence of a fearful cue, and during the evaluation of potentially threatening targets.
Keywords: Facial affect; Shared attention; Stress
Live-Virtual-Constructive (LVC) Training in Air Combat: Emergent Training Opportunities and Fidelity Ripple Effects BIBAFull-Text 82-90
  Kelly J. Neville; Angus L. M. Thom, III McLean; Sarah Sherwood; Katherine Kaste; Melissa Walwanis; Amy Bolton
Live training is where air combat personnel gain practice and experience with situations as close to real combat as possible. Computer-generated entities could expand the range and complexity of scenarios used in live training and could offer instructors a new means of manipulating the training environment. These new capabilities might help aircrew boost their proficiency beyond what is currently achieved in live training. On the other hand, computer-generated entities add artificiality to the live training environment, reducing its similarity to real combat. As part of a research program conducted to examine how the introduction of Live, Virtual, Constructive (LVC) training technology may change air combat training, we identified strategies to support learning and the acceleration of proficiency development. In this paper, we present these new possibilities for live training and discuss their implications for the fidelity of the training experience, related research, and research needs.
A Composite Cognitive Workload Assessment System in Pilots Under Various Task Demands Using Ensemble Learning BIBAKFull-Text 91-100
  Hyuk Oh; Bradley D. Hatfield; Kyle J. Jaquess; Li-Chuan Lo; Ying Ying Tan; Michael C. Prevost; Jessica M. Mohler; Hartley Postlethwaite; Jeremy C. Rietschel; Matthew W. Miller; Justin A. Blanco; Shuo Chen; Rodolphe J. Gentili
The preservation of attentional resources under mental stress holds particular importance for the execution of effective performance. Specifically, the failure to conserve attentional resources could result in an overload of attentional capacity, the failure to execute critical brain processes, and suboptimal decision-making for effective motor performance. Therefore, assessment of attentional resources is particularly important for individuals such as pilots who must retain adequate attentional reserve to respond to unexpected events when executing their primary task. This study aims to devise an expert model to assess an operator's dynamic cognitive workload in a flight simulator under various levels of challenge. The results indicate that the operator's cognitive workload can be effectively predicted with combined classifiers of neurophysiological biomarkers, subjective assessments of perceived cognitive workload, and task performance. This work provides conceptual feasibility to develop a real-time cognitive state monitoring tool that facilitates adaptive human-computer interaction in operational environments.
Keywords: Attentional reserve; Mental workload; Simulated visuomotor task; Ensemble of classifiers
Sensitive, Diagnostic and Multifaceted Mental Workload Classifier (PHYSIOPRINT) BIBAKFull-Text 101-111
  Djordje Popovic; Maja Stikic; Theodore Rosenthal; David Klyde; Thomas Schnell
Mental workload is difficult to quantify because it results from an interplay of the objective task load, ambient and internal distractions, capacity of mental resources, and strategy of their utilization. Furthermore, different types of mental resources are mobilized to a different degree in different tasks even if their perceived difficulty is the same. Thus, an ideal mental workload measure needs to quantify the degree of utilization of different mental resources in addition to providing a single global workload measure. Here we present a novel assessment tool (called PHYSIOPRINT) that derives workload measures in real time from multiple physiological signals (EEG, ECG, EOG, EMG). PHYSIOPRINT is modeled after the theoretical IMPRINT workload model developed by the US Army that recognizes seven different workload types: auditory, visual, cognitive, speech, tactile, fine motor and gross motor workload. Preliminary investigation on 25 healthy volunteers proved feasibility of the concept and defined the high level system architecture. The classifier was trained on the EEG and ECG data acquired during tasks chosen to represent the key anchors on the respective seven workload scales. The trained model was then validated on realistic driving simulator. The classification accuracy was 88.7% for speech, 86.6% for fine motor, 89.3% for gross motor, 75.8% for auditory, 76.7% for visual, and 72.5% for cognitive workload. By August of 2015, an extended validation of the model will be completed on over 100 volunteers in realistically simulated environments (driving and flight simulator), as well as in a real military-relevant environment (fully instrumented HMMWV).
Keywords: Mental workload; Assessment; EEG; IMPRINT; Wearable
The Neurobiology of Executive Function Under Stress and Optimization of Performance BIBAKFull-Text 112-123
  Ann M. Rasmusson; John M. Irvine
Much basic and clinical research to date has investigated predictors of stress resilience and vulnerability, indicating, for example, that broad impact neurobiological factors, such as neuropeptide Y (NPY) and neuroactive steroids, are mechanistically related to short term stress resilience, as well as longterm patterns of stress-related medical and neuropsychiatric comorbidities. The problem is that we lack good methods for identifying predictors of stress resilience or vulnerability at an individual level, so that human performance and therapeutic interventions can be targeted precisely to underlying points of malfunction for maximum effectiveness. We thus propose modified experimental designs that capitalize on our growing capacities to query and analyze multimodal data across the translational levels of human biology and behavior. We propose that use of these methods in studies of individuals participating in intense military training or returning from deployment could enable better prediction of performance, and development of more effective personalized interventions aimed at optimizing and maintaining stress resilience over time.
Keywords: Resilience; PTSD; Translational neuroscience; Neuropeptide Y; Allopregnanolone; Neuroactive steroids; Predictive algorithms; Functional data analysis; Non-linear modeling; Machine learning
Objective-Analytical Measures of Workload -- the Third Pillar of Workload Triangulation? BIBAKFull-Text 124-135
  Christina Rusnock; Brett Borghetti; Ian McQuaid
The ability to assess operator workload is important for dynamically allocating tasks in a way that allows efficient and effective goal completion. For over fifty years, human factors professionals have relied upon self-reported measures of workload. However, these subjective-empirical measures have limited use for real-time applications because they are often collected only at the completion of the activity. In contrast, objective-empirical measurements of workload, such as physiological data, can be recorded continuously, and provide frequently-updated information over the course of a trial. Linking the low-sample-rate subjective-empirical measurement to the high-sample-rate objective-empirical measurements poses a significant challenge. While the series of objective-empirical measurements could be down-sampled or averaged over a longer time period to match the subjective-empirical sample rate, this process discards potentially relevant information, and may produce meaningless values for certain types of physiological data. This paper demonstrates the technique of using an objective-analytical measurement produced by mathematical models of workload to bridge the gap between subjective-empirical and objective-empirical measures. As a proof of concept, we predicted operator workload from physiological data using VACP, an objective-analytical measure, which was validated against NASA-TLX scores. Strong predictive results pave the way to use the objective-empirical measures in real-time augmentation (such as dynamic task allocation) to improve operator performance.
Keywords: Workload measurement; Machine learning; VACP; IMPRINT
Eye-Tracking Technology for Estimation of Cognitive Load After Traumatic Brain Injury BIBAKFull-Text 136-143
  Ashley Safford; Jessica Kegel; Jamie Hershaw; Doug Girard; Mark Ettenhofer
The goal of this study was to develop an eye-tracking based tool to measure cognitive effort as an approach to assess injury-related changes in brain function. A set of novel tasks were developed to examine changes in manual and saccadic reaction time under varying levels of cognitive load and cuing conditions. Twenty-six healthy individuals completed these working memory and continuous monitoring tasks while eye movements were recorded. Results indicate that these tasks, in combination with eye-tracking measures, are sensitive to cognitive difficulty as manual and saccadic response times increased under the higher load and invalid cuing conditions. These procedures show promise for utility in measuring cognitive effort and track the subtle changes associated with mild TBI.
Keywords: Eye-tracking; Cognitive load; Mild TBI
Measuring Expert and Novice Performance Within Computer Security Incident Response Teams BIBAKFull-Text 144-152
  Austin Silva; Glory Emmanuel; Jonathan T. McClain; Laura Matzen; Chris Forsythe
There is a great need for creating cohesive, expert cybersecurity incident response teams and training them effectively. This paper discusses new methodologies for measuring and understanding expert and novice differences within a cybersecurity environment to bolster training, selection, and teaming. This methodology for baselining and characterizing individuals and teams relies on relating eye tracking gaze patterns to psychological assessments, human-machine transaction monitoring, and electroencephalography data that are collected during participation in the game-based training platform Tracer FIRE. We discuss preliminary findings from two pilot studies using novice and professional teams.
Keywords: Cybersecurity; Training; Teams; Visual search; Eye tracking; EEG; In situ testing; Measuring individual differences; Psychological measures
Bracketing Human Performance to Support Automation for Workload Reduction: A Case Study BIBAKFull-Text 153-163
  Robert E. Wray; Benjamin Bachelor; Randolph M. Jones; Charles Newton
Semi-automated Forces (SAFs) are commonly used in training simulation. SAFs often require human intervention to ensure that appropriate, individual training opportunities are presented to trainees. We cast this situation as a supervisory control challenge and are developing automation designed to support human operators, reduce workload, and improve training outcomes. This paper summarizes a combined analytic and empirical verification study that identified specific situations in the overall space of possible scenarios where automation may be particularly helpful. By bracketing "high performance" and "low performance" conditions, this method illuminates salient points in the space of operational performance for future human-in-the-loop studies.
Keywords: Simulation-based training; Semi-automated forces; Cognitive workload

BCI and Operational Neuroscience

Phylter: A System for Modulating Notifications in Wearables Using Physiological Sensing BIBAKFull-Text 167-177
  Daniel Afergan; Samuel W. Hincks; Tomoki Shibata; Robert J. K. Jacob
As wearable computing becomes more mainstream, it holds the promise of delivering timely, relevant notifications to the user. However, these devices can potentially inundate the user, distracting them at the wrong times and providing the wrong amount of information. As physiological sensing also becomes consumer-grade, it holds the promise of helping to control these notifications. To solve this, we build a system Phylter that uses physiological sensing to modulate notifications to the user. Phylter receives streaming data about a user's cognitive state, and uses this to modulate whether the user should receive the information. We discuss the components of the system and how they interact.
Keywords: fNIRS; Adaptive interfaces; Brain-computer interfaces; Google glass
Monitoring Mental States of the Human Brain in Action: From Cognitive Test to Real-World Simulations BIBAKFull-Text 178-186
  Deepika Dasari; Guofa Shou; Lei Ding
Functional mental state of operators in real-world workspaces is a crucial factor in many cognitively demanding tasks. In this paper, we present our recent efforts in studying electroencephalograph (EEG) biomarkers to be used to assess cognitive states of operators. We studied these biomarkers from a simple cognitive task to low- and high-fidelity simulated air traffic control (ATC) tasks, with both novices and professional ATC operators. EEG data were recorded from 25 subjects (in three studies) who performed one of three different cognitively demanding tasks up to 120 min. Our results identified two EEG components with similar spatial and spectral patterns at the group level across all three studies, which both indicated the time-on-task effects in their temporal dynamics. With further developments in the future, the technology and identified biomarkers can be used for real-time monitoring of operators' cognitive functions in critical task environments and may even provide aids when necessary.
Keywords: Functional brain imaging; EEG; Independent component analysis; Mental state; Human factors
Discrimination in Good-Trained Brain States for Brain Computer Interface BIBAKFull-Text 187-198
  Mariko Funada; Tadashi Funada; Yoshihide Igarashi
BCI (brain computer interface) is particularly important for HCI. Some of recent results concerning BCI made a great contribution to the development of the HCI research area. In this paper we define "good-trained brain states", and then propose a method for discriminating good-trained brain states from other states. We believe that repetitious training might be effective to human brains. Human brain reactions can be quantified by ERPs (event related potentials). We analyze the data of ERPs reflecting the brain reactions, and then discuss the effect of repetitious training to the brain states.
Keywords: Good-trained brain states; BCI; ERP; EEG; Individual difference
BCI and Eye Gaze: Collaboration at the Interface BIBAKFull-Text 199-210
  Leo Galway; Chris Brennan; Paul McCullagh; Gaye Lightbody
Due to an extensive list of restraints, brain-computer interface (BCI) technology has seen limited success outside of laboratory conditions. In order to address these limitations, which have prevented widespread deployment, an existing modular architecture has been adapted to support hybrid collaboration of commercially available BCI and eye tracking technologies. However, combining multiple input modalities, which have different temporal properties, presents a challenge in terms of data fusion and collaboration at the user interface. The use of cost-effective and readily available equipment will further promote hybrid BCI as a viable but alternative interface for human computer interaction. In this paper, we focus on navigation through a virtual smart home and control of devices within the rooms; the navigation being controlled by multimodal interaction. As such, it promises a better information transfer rate than BCI alone. Consequently, an extended architecture for a personalised hybrid BCI system has been proposed.
Keywords: Hybrid brain-computer interface; Eye tracking; Domotic control modalities
Using Behavioral Information to Contextualize BCI Performance BIBAKFull-Text 211-220
  Stephen M. Gordon; Jonathan R. McDaniel; Jason S. Metcalfe; Antony D. Passaro
Brain-computer interface (BCI) systems often require millisecond-level timing precision in order to function reliably. However, as BCI research expands to an ever-widening array of applications, including operation in real-world environments, such timing requirements will need to be relaxed. In addition, overall BCI system design must be improved in order to better disambiguate the numerous, seemingly similar, neural responses that may arise in such environments. We argue that this new area of operational BCI will require the integration of neural data with non-neural contextual variables in order to function reliably. We propose a framework in which non-neural contextual information can be used to better scope the operational BCI problem by indicating windows of time for specific analyses as well as defining probability distributions over these windows. We demonstrate the utility of our framework on a sample data set and provide discussion on many of the factors influencing performance.
Keywords: Brain-computer interface (BCI); Electroencephalography (EEG); Asynchronous event detection
How Low Can You Go? Empirically Assessing Minimum Usable DAQ Performance for Highly Fieldable EEG Systems BIBAFull-Text 221-231
  W. David Hairston; Vernon Lawhern
Electroencephalography (EEG) as a physiological assessment technique holds high promise for on-line monitoring of cognitive states. Examples include detecting when a user is overly fatigued, if they are paying attention to a target item, or even detecting sub-conscious object recognition, all of which can be used for greatly enhanced human-system interaction. However, because EEG involves measuring extremely small voltage fluctuations (microvolts) against a potential background that is very large (milivolts), conventional EEG data acquisition (DAQ) systems utilize very high-resolution components, such as low-noise amplifiers and 24-bit sigma-delta analog-to-digital converters (ADCs) on the ideal premise of acquiring a maximal resolution signal to guarantee information content from the data. Unfortunately this comes at the cost of high power consumption and requires expensive system components. We hypothesize that, for many targeted research applications, this level of resolution may not be necessary, and that by intelligently allowing a reduction in the signal fidelity, substantial savings in cost and power consumption can be obtained. To date though a pragmatic minimum resolution remains unexplored. Here, we discuss the utility of using a parametric approach of simulating signal degradation analogous to decreasing ADC bit (vertical) resolution and amplifier fidelity. Results derived from classification of both drowsiness (alpha oscillation) and oddity (P300) detection show strong overall robustness to poor-quality signals, such that classifier performance remains unaffected until resolution is well outside of typical recording specifications. These observations suggest that researchers and system designers should carefully consider that resolution trade-offs for power and cost are entirely reasonable for targeted applications, enabling feasibility of ultra-low power or highly fieldable data collection systems in the near future.
Investigation of Functional Near Infrared Spectroscopy in Evaluation of Pilot Expertise Acquisition BIBAKFull-Text 232-243
  Gabriela Hernandez-Meza; Lauren Slason; Hasan Ayaz; Patrick Craven; Kevin Oden; Kurtulus Izzetoglu
Functional Near-Infrared (fNIR) spectroscopy is an optical brain imaging technology that enables assessment of brain activity through the intact skull in human subjects. fNIR systems developed during the last decade allow for a rapid, non-invasive method of measuring the brain activity of a subject while conducting tasks in realistic environments. This paper examines the hemodynamic changes associated with expertise development during C-130j simulated flying missions.
Keywords: Near-infrared spectroscopy; Optical brain imaging; fNIR; Human performance assessment; Pilot training
Measuring Situational Awareness Aptitude Using Functional Near-Infrared Spectroscopy BIBAKFull-Text 244-255
  Leanne Hirshfield; Mark Costa; Danushka Bandara; Sarah Bratt
Attempts have been made to evaluate people's situational awareness (SA) in military and civilian contexts through subjective surveys, speed, and accuracy data acquired during SA target tasks. However, it is recognized in the SA domain that more systematic measurement is necessary to assess SA theories and applications. Recent advances in biomedical engineering have enabled relatively new ways to measure cognitive and physiological state changes, such as with functional near-infrared spectroscopy (fNIRS). In this paper, we provide a literature review relating to SA and fNIRS and present an experiment conducted with an fNIRS device comparing differences in the brains between people with high and low SA aptitude. Our results suggest statistically significant differences in brain activity between the high SA group and low SA group.
Keywords: Situational awareness; fNIRS; HCI; Brain measurement
Neurocognitive Correlates of Learning in a Visual Object Recognition Task BIBAKFull-Text 256-267
  Ion Juvina; Priya Ganapathy; Matt Sherwood; Mohd Saif Usmani; Gautam Kunapuli; Tejaswi Tamminedi; Nasser Kashou
Preliminary results of a longitudinal study aimed at understanding the neurocognitive correlates of learning in a visual object recognition task are reported. The experimental task used real-world novel stimuli, whereas the control task used real-world familiar stimuli. Participants practiced the tasks over 10 weeks and reached a high level of accuracy. Brain imaging data was acquired in weeks 2, 6, and 10 and eye-tracking data was acquired in the other seven weeks. Quantitative and qualitative changes in brain activity were observed over the course of learning and skill acquisition. Generally, in the experimental task, brain activity increased at week 6 and decreased at week 10, whereas in the control task, brain activity decreased at week 6 and further decreased at week 10 compared to week 2. New clusters of brain activity emerged at week 6 in the experimental task. Eye-fixation and pupil-dilation data showed that fast learners tend to inspect the stimuli more thoroughly even after a response was given. These results are used to inform the development of computational cognitive models of visual object recognition tasks.
Keywords: Longitudinal study; Learning; Brain imaging; Eye tracking
Neural Adaptation to a Working Memory Task: A Concurrent EEG-fNIRS Study BIBAKFull-Text 268-280
  Yichuan Liu; Hasan Ayaz; Banu Onaral; Patricia A. Shewokis
Simultaneously recorded electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) measures from sixteen subjects were used to assess neural correlates of a letter based n-back working memory task. We found that EEG alpha power increased and prefrontal cortical oxygenation decreased with increased practice time for the high memory load condition (2-back), suggesting lower brain activation and a tendency toward the 'idle' state. The cortical oxygenation changes for the low memory load conditions (0-back and 1-back) changed very little throughout the training session which the behavioral scores showed high accuracy and a ceiling effect. No significant effect of practice time were found for theta power or the behavioral performance measures.
Keywords: Multimodality; EEG; fNIRS; Working memory; Mental workload; Practice time; Adaptation
The Effect of Limiting Trial Count in Context Aware BCIs: A Case Study with Language Model Assisted Spelling BIBAFull-Text 281-292
  Mohammad Moghadamfalahi; Paula Gonzalez-Navarro; Murat Akcakaya; Umut Orhan; Deniz Erdogmus
Deflections in recorded electroencephalography (EEG) in response to visual, auditory or tactile stimuli have been popularly employed in non-invasive EEG based brain computer interfaces (BCIs) for intent detection. For example, in an externally stimulated typing BCI, an accurate estimate of the user intent might require long EEG data collection before the system can make a decision with a desired confidence. Long decision period can lead to slow typing and hence the user frustration. Therefore, there is a trade-off between the accuracy of inference and the typing speed. In this manuscript, using Monte-Carlo simulations, we assess the speed and accuracy of a Language Model (LM) assisted non-invasive EEG based typing BCI, RSVPKeyboard™, as a function of the maximum number of repetitions of visual stimuli sequences and the inter-trial interval (ITI) within the sequences. We show that the best typing performance with RSVPKeyboard™can be obtained when ITI=150 ms and maximum number of allowed sequences is 8. Even though the probabilistic fusion of the language model with the EEG evidence for joint inference allows the RSVPKeyboard™ to perform auto-typing when the system is confident enough t o make decisions before collecting EEG evidence, our experimental results show that RSVPKeyboard™does not benefit from auto-typing.
Improving BCI Usability as HCI in Ambient Assisted Living System Control BIBAKFull-Text 293-303
  Niccolò Mora; Ilaria De Munari; Paolo Ciampolini
Brain Computer Interface (BCI) technology is an alternative/augmentative communication channel, based on the interpretation of the user's brain activity, who can then interact with the environment without relying on neuromuscular pathways. Such technologies can act as alternative HCI devices towards AAL (Ambient Assisted Living) systems, thus opening their services to people for whom interacting with conventional interfaces could be troublesome, or even not viable. We present here a complete solution for BCI-enabled home automation. The implemented solution is, nonetheless, more general in the approach, since both the realized hardware module and the software infrastructure can handle general bio-potentials. We demonstrate the effectiveness of the solution by restricting the focus to a SSVEP-based, self-paced BCI, featuring calibration-less operation and a subject-independent, "plug&play" approach. The hardware module will be validated and compared against a commercial EEG device; at the same time, the signal processing chain will be presented, introducing a novel method for improving accuracy and immunity to false positives. The results achieved, especially in terms of false positive rate containment (0.26 min-1) significantly improve over the literature.
Keywords: Brain computer interface (BCI); Steady state visual evoked potential (SSVEP); Self-paced BCI; Subject-independent BCI
Human Computer Confluence in BCI for Stroke Rehabilitation BIBAFull-Text 304-312
  Rupert Ortner; Danut-Constantin Irimia; Christoph Guger; Günter Edlinger
This publication presents a novel device for BCI based stroke rehabilitation, using two feedback modalities: visually, via an avatar showing the desired movements in the user's first perspective; and via electrical stimulation of the relevant muscles. Three different kinds of movements can be trained: wrist dorsiflexion, elbow flexion and knee extension. The patient has to imagine the selected motor movements. Feedback is presented online by the device if the BCI detects the correct imagination. Results of two patients are presented showing improvements in motor control for both of them.
Relevant HCI for Hybrid BCI and Severely Impaired Patients BIBAKFull-Text 313-323
  José Rouillard; Alban Duprès; François Cabestaing; Marie-Hélène Bekaert; Charlotte Piau; Christopher Coat; Jean-Marc Vannobel; Claudine Lecocq
In this paper, we are studying the possibility to enhance the relevance of hybrid Brain-Computer Interfaces for severely impaired patients by improving the relevance of Human-Computer Interfaces. Across virtual reality tools and serious games approaches, we believe that users will be more able to understand how to interact with such kind of interactive systems.
Keywords: Human-computer interaction; BCI; Hybrid BCI; Handicap; Virtual reality
Brain-in-the-Loop Learning Using fNIR and Simulated Virtual Reality Surgical Tasks: Hemodynamic and Behavioral Effects BIBAKFull-Text 324-335
  Patricia A. Shewokis; Hasan Ayaz; Lucian Panait; Yichuan Liu; Mashaal Syed; Lawrence Greenawald; Faiz U. Shariff; Andres Castellanos; D. Scott Lind
Functional near infrared spectroscopy (fNIR) is a noninvasive, portable optical imaging tool to monitor changes in hemodynamic responses (i.e., oxygenated hemoglobin (HbO)) within the prefrontal cortex (PFC) in response to sensory, motor or cognitive activation. We used fNIR for monitoring PFC activation during learning of simulated laparoscopic surgical tasks throughout 4 days of training and testing. Blocked (BLK) and random (RND) practice orders were used to test the practice schedule effect on behavioral, hemodynamic responses and relative neural efficiency (EFFrel-neural) measures during transfer. Left and right PFC for both tasks showed significant differences with RND using less HbO than BLK. Cognitive workload showed RND exhibiting high EFFrel-neural across the PFC for the coordination task while the more difficult cholecystectomy task showed EFFrel-neural differences only in the left PFC. Use of brain activation, behavioral and EFFrel-neural measures can provide a more accurate depiction of the generalization or transfer of learning.
Keywords: Cognitive effort and learning; fNIR; Simulation; Virtual reality; Transfer; Brain sensors and measures; Contextual interference
Team Resilience: A Neurodynamic Perspective BIBAKFull-Text 336-347
  Ronald Stevens; Trysha Galloway; Jerry Lamb; Ronald Steed; Cynthia Lamb
Neurophysiologic models were created from US Navy navigation teams performing required simulations that captured their dynamic responses to the changing task environment. Their performances were simultaneously rated by two expert observers for team resilience using a team process rubric adopted by the US Navy Submarine Force. Symbolic neurodynamic (NS) representations of the 1-40 Hz EEG amplitude fluctuations of the crew were created each second displaying the EEG levels of each team member in the context of the other crew members and in the context of the task. Quantitative estimates of the NS fluctuations were made using a moving window of entropy. Periods of decreased entropy were considered times of increased team neurodynamic organization; e.g. when there were prolonged and restricted relationships between the EEG- PSD levels of the crew. Resilient teams showed significantly greater neurodynamic organization in the pre-simulation Briefing than the less resilient teams. Most of these neurodynamic organizations occurred in the 25-40 Hz PSD bins. In contrast, the more resilient teams showed significantly lower neurodynamic organization during the Scenario than the less resilient teams with the greatest differences in the 12-20 Hz PSD bins. The results indicate that the degree of neurodynamic organization reflects the performance dynamics of the team with more organization being important during the pre-mission briefing while less organization (i.e. more flexibility) important while performing the task.
Keywords: Team neurodynamics; Resilience; EEG; Submarine
Through a Scanner Quickly: Elicitation of P3 in Transportation Security Officers Following Rapid Image Presentation and Categorization BIBAKFull-Text 348-360
  Michael C. Trumbo; Laura E. Matzen; Austin Silva; Michael J. Haass; Kristin Divis; Ann Speed
Numerous domains, ranging from medical diagnostics to intelligence analysis, involve visual search tasks in which people must find and identify specific items within large sets of imagery. These tasks rely heavily on human judgment, making fully automated systems infeasible in many cases. Researchers have investigated methods for combining human judgment with computational processing to increase the speed at which humans can triage large image sets. One such method is rapid serial visual presentation (RSVP), in which images are presented in rapid succession to a human viewer. While viewing the images and looking for targets of interest, the participant's brain activity is recorded using electroencephalography (EEG). The EEG signals can be time-locked to the presentation of each image, producing event-related potentials (ERPs) that provide information about the brain's response to those stimuli. The participants' judgments about whether or not each set of images contained a target and the ERPs elicited by target and non-target images are used to identify subsets of images that merit close expert scrutiny [1]. Although the RSVP/EEG paradigm holds promise for helping professional visual searchers to triage imagery rapidly, it may be limited by the nature of the target items. Targets that do not vary a great deal in appearance are likely to elicit useable ERPs, but more variable targets may not. In the present study, we sought to extend the RSVP/EEG paradigm to the domain of aviation security screening, and in doing so to explore the limitations of the technique for different types of targets. Professional Transportation Security Officers (TSOs) viewed bag X-rays that were presented using an RSVP paradigm. The TSOs viewed bursts of images containing 50 segments of bag X-rays that were presented for 100 ms each. Following each burst of images, the TSOs indicated whether or not they thought there was a threat item in any of the images in that set. EEG was recorded during each burst of images and ERPs were calculated by time-locking the EEG signal to the presentation of images containing threats and matched images that were identical except for the presence of the threat item. Half of the threat items had a prototypical appearance and half did not. We found that the bag images containing threat items with a prototypical appearance reliably elicited a P300 ERP component, while those without a prototypical appearance did not. These findings have implications for the application of the RSVP/EEG technique to real-world visual search domains.
Keywords: Rapid serial visual presentation; Visual search; EEG; P300
Constrained Tensor Decomposition via Guidance: Increased Inter and Intra-Group Reliability in fMRI Analyses BIBAKFull-Text 361-369
  Peter B. Walker; Sean Gilpin; Sidney Fooshee; Ian Davidson
Recently, Davidson and his colleagues introduced a promising new approach to analyzing functional Magnetic Resonance Imaging (fMRI) that suggested a more appropriate analytic approach is one that views the spatial and temporal activation as a multi-way tensor [1]. In this paper, we illustrate how the use of prior domain knowledge might be incorporated into the deconstruction of the tensor so as to increase analytical reliability. These results will be discussed in reference to implications towards military selection and classification.
Keywords: Tensor decomposition; Functional magnetic resonance imaging; Reliability

Cognition, Perception and Emotion Measurement

A Quantitative Methodology for Identifying Attributes Which Contribute to Performance for Officers at the Transportation Security Administration BIBAKFull-Text 373-380
  Glory Emmanuel; Robert Kittinger; Ann Speed
Performance at Transportation Security Administration (TSA) airport checkpoints must be consistently high to skillfully mitigate national security threats and incidents. To accomplish this, Transportation Security Officers (TSOs) must exceptionally perform in threat detection, interaction with passengers, and efficiency. It is difficult to measure the human attributes that contribute to high performing TSOs because cognitive ability such as memory, personality, and competence are inherently latent variables. Cognitive scientists at Sandia National Laboratories have developed a methodology that links TSOs' cognitive ability to their performance. This paper discusses how the methodology was developed using a strict quantitative process, the strengths and weaknesses, as well as how this could be generalized to other non-TSA contexts. The scope of this project is to identify attributes that distinguished high and low TSO performance for the duties at the checkpoint that involved direct interaction with people going through the checkpoint.
Keywords: Measuring and adapting to individual differences; Cognitive modeling; Perception; Emotion and interaction; Quantifying latent variables
Cognitive-Motor Processes During Arm Reaching Performance Through a Human Body-Machine Interface BIBAKFull-Text 381-392
  Rodolphe J. Gentili; Isabelle M. Shuggi; Kristen M. King; Hyuk Oh; Patricia A. Shewokis
Head controlled based systems represent a class of human body-machine interfaces that employ head motion to control an external device. Overall, the related work has focused on technical developments with limited user performance assessments while generally ignoring the underlying motor learning and cognitive processes. Thus, this study examined, during and after practice, the cognitive-motor states of users when controlling a robotic arm with limited head motion under various control modalities. As a first step, two groups having a different degree of control of the arm directions were considered. The preliminary results revealed that both groups: (i) similarly improved their reaching performance during practice; (ii) provided, after practice, a similar performance generalization while still relying on visual feedback and (iii) exhibited similar cognitive workload. This work can inform the human cognitive-motor processes during learning and performance of arm reaching movements as well as develop rehabilitation systems for disabled individuals.
Keywords: Cognitive-motor performance; Arm reaching movements; Motor practice and learning; Cognitive workload; Human body-machine interface; Robotic arm; Motor rehabilitation
How Mobile Phones Affect the Sustainability of the Work/Life Balance of Their Users BIBAKFull-Text 393-400
  Edward Peter Greenwood White; Andrew Thatcher
This study examined the relationship between sustainability of mobile phone users and work-life balance. Twenty-seven interviews were performed on managerial level mobile phone owners over the duration of a month and half. The study extends Clark's [1] original Border theory that fails to mention how mobile phones (or indeed any other information and communication technology) influence the borders between the two domains. This study found technology has a definitive impact with separate users groups emerging from the data; border-extenders, border-adapters and border-enforcers.
Keywords: Border theory; Mobile phone usage; Mobile phone usage patterns; Work sustainability; Home-work balance; Work-home interface; Mobile phone after-hours work; After-hours work
Methodology for Knowledge Elicitation in Visual Abductive Reasoning Tasks BIBAKFull-Text 401-409
  Michael J. Haass; Laura E. Matzen; Susan M. Stevens-Adams; Allen R. Roach
The potential for bias to affect the results of knowledge elicitation studies is well recognized. Researchers and knowledge engineers attempt to control for bias through careful selection of elicitation and analysis methods. Recently, the development of a wide range of physiological sensors, coupled with fast, portable and inexpensive computing platforms, has added an additional dimension of objective measurement that can reduce bias effects. In the case of an abductive reasoning task, bias can be introduced through design of the stimuli, cues from researchers, or omissions by the experts. We describe a knowledge elicitation methodology robust to various sources of bias, incorporating objective and cross-referenced measurements. The methodology was applied in a study of engineers who use multivariate time series data to diagnose the performance of devices throughout the production lifecycle. For visual reasoning tasks, eye tracking is particularly effective at controlling for biases of omission by providing a record of the subject's attention allocation.
Keywords: Knowledge elicitation; Eye tracking; Abductive reasoning
Stability of a Type of Cross-Cultural Emotion Modeling in Social Media BIBAFull-Text 410-417
  Monte Hancock; Chad Sessions; Chloe Lo; Shakeel Rajwani; Elijah Kresses; Cheryl Bleasdale; Dan Strohschein
Humankind has thousands of years of experience in assessing the emotional context of face-to-face interaction. Written communication has been refined over centuries, and imme-diate voice communication over decades. However, online communication, which tends to be asynchronous and largely empty of conventional social cues, is still emerging as a cultural and cognitive venue. In this paper we present the earliest results of applying our field-theory of "emotional context" to the problem of the cross-cultural online emotion modeling:
   Can a field-theoretic model developed using data from one culture be applied to online interaction in another?
   We also present the results of a small empirical study focusing on the methods we used to visualize and model the "emotional context" of a social media corpus.
Field-Theoretic Modeling Method for Emotional Context in Social Media: Theory and Case Study BIBAFull-Text 418-425
  Monte Hancock; Shakeel Rajwani; Chloe Lo; Suraj Sood; Elijah Kresses; Cheryl Bleasdale; Nathan Dunkel; Elise Do; Gareth Rees; Jared Steirs; Christopher Romero; Dan Strohschein; Keith Powell; Rob French; Nicholas Fedosenko; Chris Casimir
Just as masses and charges give rise to gravitational and electric fields, the online behaviors of individuals engaged in online social discourse give rise to an "emotional context" that conditions, and is conditioned by, these behaviors. Using Information Geometry and Unsupervised Learning, we have formulated a mathematical field theory for modeling online emotional context. This theory has been used to create a soft-ware application, Sirius15, that infers, characterizes, and visualizes the field structure ("emotional context") arising from this discourse. A mathematical approach is presented to social media modeling that enables automated characterization and analysis of the emotional context associated with social media interactions. The results of a small, preliminary case study carried out by our team are presented.
A Neurocognitive Approach to Expertise in Visual Object Recognition BIBAKFull-Text 426-436
  Assaf Harel
How can we enhance the ability of observers to pick-up visual information? One approach to this question has been to investigate people who naturally develop an exceptional skill, or expertise, in visual object recognition (e.g. bird watchers, car buffs), and determine how expert processing and the neural substrates supporting it differ from those in novices. The present paper will describe the mainstream view of visual expertise, which considers it to be an automatic, stimulus-driven perceptual skill that is supported by specific regions in high-level visual cortex. Following a critical review of the perceptual framework of expertise, a series of neuroimaging studies will be presented which reveal that in contrast to the mainstream view, visual expertise emerges from multiple interactions within and between the visual system and other cognitive systems (e.g. top-down attention and conceptual memory). These interactions are manifest in widespread distributed patterns of activity across the entire cortex, and are highly susceptible to high-level factors, such as task relevance and prior knowledge. Lastly, the applied and theoretical implications of the interactive framework to performance enhancement and neuroplasticity will be discussed.
Keywords: Expertise; Object recognition; Vision; Top-down control; fMRI
Augmenting Bioacoustic Cognition with Tangible User Interfaces BIBAKFull-Text 437-448
  Isak Herman; Leonardo Impett; Patrick K. A. Wollner; Alan F. Blackwell
Using a novel visualization and control interface -- the Mephistophone -- we explore the development of a user interface for acoustic visualization and analysis of bird calls. Our intention is to utilize embodied computation as an aid to acoustic cognition. The Mephistophone demonstrates 'mixed initiative' design, where humans and systems collaborate toward creative and purposeful goals. The interaction modes of our prototype allow the dextral manipulation of abstract acoustic structure. Combining information visualization, timbre-space exploration, collaborative filtering, feature learning, and human inference tasks, we examine the haptic and visual affordances of a 2.5D tangible user interface (TUI). We explore novel representations in the audial representation-space and how a transition from spectral to timbral visualization can enhance user cognition.
Keywords: Tangible user interfaces; Embodied interaction; Bioacoustics; Information visualization; Collaborative filtering
Predicting Learner Performance Using a Paired Associate Task in a Team-Based Learning Environment BIBAKFull-Text 449-460
  Othalia Larue; Ion Juvina; Gary Douglas; Albert Simmons
In this paper, we use a computational cognitive model to make a priori predictions for an upcoming human study. Model predictions are generated in conditions identical to those that human participants will be placed in. Models were built in a computational cognitive architecture, which implements a theory of human cognition, ACT-R (Adaptive Control of Thought -- Rational) (Anderson, 2007). The experiment contains three conditions: lecture, interactive lecture, and team-based learning (TBL). Team-based learning has been shown to improve performance compared to the classical non-interactive lecture. Our model predicted the same outcome. It also predicted that players in the TBL condition would perform better than players in the interactive lecture condition.
Keywords: Cognitive modeling; Team-based learning; A priori model prediction
Exploring Day-to-Day Variability in the Relations Between Emotion and EEG Signals BIBAKFull-Text 461-469
  Yuan-Pin Lin; Sheng-Hsiou Hsu; Tzyy-Ping Jung
Electroencephalography (EEG)-based emotion classification has drawn increasing attention over the last few years and become an emerging direction in brain-computer interfaces (BCI), namely affective BCI (ABCI). Many prior studies devoted to improve emotion-classification models using the data collected within a single session or day. Less attention has been directed to the day-to-day EEG variability associated with emotional responses. This study recorded EEG signals of 12 subjects, each underwent the music-listening experiment on five different days, to assess the day-to-day variability from the perspectives of inter-day data distributions and cross-day emotion classification. The empirical results of this study demonstrated that the clusters of the same emotion across days tended to scatter wider than the clusters of different emotions within a day. Such inter-day variability poses a severe challenge for building an accurate cross-day emotion-classification model in real-life ABCI applications.
Keywords: EEG-based emotion classification; Day-to-day variability
Integration and Disintegration of Auditory Images Perception BIBAKFull-Text 470-480
  Sergei Lytaev; Ksenia Belskaya
Defects of sensory perception are one of essential features in structure of psychopathological frustration. The conscious mental activity includes components of perception, construction of an image, memory and thought processes. The perception is formed on the basis of synthesis of three kinds of the information flows: sensory, taken from memory and coming from the centers of motivation. The sensory information defines communication of cognition with an external world. Purpose of present research was aimed for studying character and a degree of disorders of mechanisms of perception and integration of auditory figurative information at depressive psychopathological states. Outcomes of present research, including EEG coherent analysis, represent convincing acknowledgement of brain decomposition at perception of the auditory information at patients with psychopathological frustration.
Keywords: Sensory perception; Auditory images (AI); EEG; Decision-making
Effects of Professional Visual Search Experience on Domain-General and Domain-Specific Visual Cognition BIBAKFull-Text 481-491
  Laura E. Matzen; Michael J. Haass; Laura A. McNamara; Susan M. Stevens-Adams; Stephanie N. McMichael
Vision is one of the dominant human senses and most human-computer interfaces rely heavily on the capabilities of the human visual system. An enormous amount of effort is devoted to finding ways to visualize information so that humans can understand and make sense of it. By studying how professionals engage in these visual search tasks, we can develop insights into their cognitive processes and the influence of experience on those processes. This can advance our understanding of visual cognition in addition to providing information that can be applied to designing improved data visualizations or training new analysts.
   In this study, we investigated the role of expertise on performance in a Synthetic Aperture Radar (SAR) target detection task. SAR imagery differs substantially from optical imagery, making it a useful domain for investigating expert-novice differences. The participants in this study included professional SAR imagery analysts, radar engineers with experience working with SAR imagery, and novices who had little or no prior exposure to SAR imagery. Participants from all three groups completed a domain-specific visual search task in which they searched for targets within pairs of SAR images. They also completed a battery of domain-general visual search and cognitive tasks that measured factors such as mental rotation ability, spatial working memory, and useful field of view. The results revealed marked differences between the professional imagery analysts and the other groups, both for the domain-specific task and for some domain-general tasks. These results indicate that experience with visual search in non-optical imagery can influence performance on other domains.
Keywords: Visual search; Expertise
Ethnographic Methods for Experimental Design: Case Studies in Visual Search BIBAKFull-Text 492-503
  Laura A. McNamara; Kerstan Cole; Michael J. Haass; Laura E. Matzen; J. Daniel Morrow; Susan M. Stevens-Adams; Stephanie McMichael
Researchers at Sandia National Laboratories are integrating qualitative and quantitative methods from anthropology, human factors and cognitive psychology in the study of military and civilian intelligence analyst workflows in the United States' national security community. Researchers who study human work processes often use qualitative theory and methods, including grounded theory, cognitive work analysis, and ethnography, to generate rich descriptive models of human behavior in context. In contrast, experimental psychologists typically do not receive training in qualitative induction, nor are they likely to practice ethnographic methods in their work, since experimental psychology tends to emphasize generalizability and quantitative hypothesis testing over qualitative description. However, qualitative frameworks and methods from anthropology, sociology, and human factors can play an important role in enhancing the ecological validity of experimental research designs.
Keywords: Visual search; Qualitative methods; Experimental design; Synthetic aperture radar; Imagery analysis
Removal of Ocular Artifacts with the Utilization of Filter Banks BIBAKFull-Text 504-513
  Umut Orhan; Santosh Mathan
Eye blinks and other ocular artifacts represent a dominant source of EEG signal interference, especially in frontal EEG electrodes. Even though there are several widely accepted methods for the removal eye-blinks, (e.g. linear filtering and ICA), it is still a difficult problem to address when the number of EEG electrodes are limited (as is the case for EEG systems designed for everyday application contexts), and dedicating a subset of these for monitoring eye activity is impractical. In this paper, we propose a novel and general method to eliminate the ocular artifacts based on a combination of filter banks and an eye tracker. This approach offers the promise of making non-intrusive, efficient, and robust ocular artifact detection and correction a tractable prospect.
Keywords: Artifacts; EEG; Ocular; Filter banks; Filtering
The Quantified Self BIBAFull-Text 514-520
  Celementina R. Russo
Over the course of this decade, both mobile devices and mobile device applications designed for the express purpose of tracking physiological and cognitive performance metrics are nearly ubiquitous in our everyday endeavors. Though the idea of tracking our own various daily metrics is nothing new, the advent of technological innovations that carry the capacity to store, sort and share these ever-accruing amounts of data presents to us uncharted territory regarding our relationship to and understanding and interpretation of these metrics both singularly (as snapshots) and in the aggregate (over time). This work explores the form and function of the Quantified Self Movement. It discusses the current state of analyzing and interpreting information accrued from various metrics, specifically the issues that arise in synchronizing heterogeneous metrics, and in the context of an AugCog framework, proposes a method of approach to analyze multivariate data by curation based on the simultaneity of measured events.
Adapting Ethics for Future Technologies BIBAKFull-Text 521-527
  Todd Seech
From the handheld tools of the first humans to the latest computer interfaces, technology has augmented our perceptions and interactions with each other and the world around us. Each new generation is born into its own evolution of technological advancements with seemingly preprogrammed literacy in the scientific innovation of the day. These novel technologies are examples of science's fluid nature and linear progression, which drive researchers to produce the next life-changing advancement as quickly as possible. However, rapid and unbridled scientific advancement can veil unacceptable ethical pitfalls. Therefore, the speed with which technology advances must be matched with complementary development of ethical principles. The present paper applies this concept to a handful of modern and near-future technologies that represent paradigm changes to science as well as to everyday life. The paper then explores ethical issues that may arise from these technologies and presents an outline for a new ethical framework.
Keywords: Ethics; Cognitive augmentation; Genetics
Visual Search in Operational Environments BIBAKFull-Text 528-536
  Ann Speed
Visual search has been an active area of research -- empirically and theoretically -- for a number of decades, however much of that work is based on novice searchers performing basic tasks in a laboratory. This paper summarizes some of the issues associated with quantifying expert, domain-specific visual search behavior in operationally realistic environments.
Keywords: Visual search; Expertise; Domain specific tasks; Ecological validity; Operational environments
Exploratory Analysis of Visual Search Data BIBAKFull-Text 537-547
  David J. Stracuzzi; Ann Speed; Austin Silva; Michael Haass; Derek Trumbo
Visual search data describe people's performance on the common perceptual problem of identifying target objects in a complex scene. Technological advances in areas such as eye tracking now provide researchers with a wealth of data not previously available. The goal of this work is to support researchers in analyzing this complex and multimodal data and in developing new insights into visual search techniques. We discuss several methods drawn from the statistics and machine learning literature for integrating visual search data derived from multiple sources and performing exploratory data analysis. We ground our discussion in a specific task performed by officers at the Transportation Security Administration and consider the applicability, likely issues, and possible adaptations of several candidate analysis methods.
Keywords: Visual search; Eye tracking; Data analysis; Transportation Security Administration

Adaptive Tutoring and Training

Transitioning from Human to Agent-Based Role-Players for Simulation-Based Training BIBAKFull-Text 551-561
  Robert G. Abbott; Christina Warrender; Kiran Lakkaraju
In the context of military training simulation, "semi-automated forces" are software agents that serve as role players. The term implies a degree of shared control -- increased automation allows one operator to control a larger number of agents, but too much automation removes control from the instructor. The desired amount of control depends on the situation, so there is no single "best" level of automation. This paper describes the rationale and design for Trainable Automated Forces (TAF), which is based on training by example in order to reduce the development time for automated agents. A central issue is how TAF interprets demonstrated behaviors either as an example to follow specifically, or as contingencies to be executed as the situation permits. We describe the behavior recognizers that allow TAF to produce a high-level model of behaviors. We assess the accuracy of a recognizer for a simple airplane maneuver, showing that it can accurately recognize the maneuver from just a few examples.
Keywords: Learning by example; Training by demonstration; Software agents
Authoring Tools for Adaptive Training -- An Overview of System Types and Taxonomy for Classification BIBAFull-Text 562-569
  Keith Brawner
The Intelligent Tutoring Systems (ITS) community has recently renewed its interest in authoring tools, as evidenced in recent workshops, publications, and developments. Part of this renewal of effort has been in the development of authoring tools systems for maturing products and processes. As an example, the Cognitive Tutor Authoring Tools (CTAT), AutoTutor Script Authoring Tools (ASAT), and Generalized Intelligent Framework for Tutoring (GIFT) Authoring Tool (GAT) are all available for community use and feedback through their various portals. As these authoring tools come available, it is helpful to classify them into groups, for the purpose of study, based upon their similarities and differences.
Prolonged Physical Effort Affects Cognitive Processes During Special Forces Training BIBAKFull-Text 570-582
  Clayton A. Domingues; Esmaela C. P. Domingues; Osvaldo J. Nascimento; Nilton G. Rolim Filho; Jorge T. Annunziato; Jorge L. C. Rebelo; Seth R. Nieman; Kyle J. Jaquess; Rodolphe J. Gentili; Bradley D. Hatfield
This study aimed to investigate the effects of strenuous physical exertion on biomarkers of muscle damage, on physical and mental fatigue, and on cognitive processes. Seventeen military (males 24-40 years old) were tested cognitively at six time points, while they were progressively exhausted over the course of 102 h of continued operations. Three types of variables were analyzed: biomarkers of muscle damage [serum levels of creatine kinase (CK) and lactate dehydrogenase (LDH)], reported physical fatigue (PF) and mental fatigue (MF), and cognitive processes [(verbal reasoning (VR), numerical reasoning (NR) and spatial reasoning (SR) and short-term memory (STM)]. The results revealed significant increases in CK, LDH, PF and MF. On the other hand, we found significant decreases in VR, NR, SR and STM, which were negatively correlated MF. Our results show additional evidences about the impact of strenuous physical exertion on muscle damage, physical and mental fatigue, and cognitive processes.
Keywords: Strenuous physical exertion; Physical fatigue; Mental fatigue; Cognitive processes; Continued operations
Development of a Smart Tutor for a Visual-Aircraft Recognition Task BIBAKFull-Text 583-594
  Priya Ganapathy; Ion Juvina; Tejaswi Tamminedi; Gautam Kunapuli; Matt Sherwood; Mohd Saif Usmani
The goal of this project is to design an intelligent tutor to teach visual aircraft recognition (VACR) skills to military population. Under extreme cognitive demand, soldiers must learn to rapidly recognize and identify the aircraft prior to engagement. The goal of the smart tutor is to train the trainees to look at specific features (called Wings, Engine, Fuselage and Tail -- WEFT) of the aircraft that will help them proceduralize the skill of aircraft recognition.
   We have conducted an empirical (fMRI, eye-tracking, behavior) study and developed a cognitive model based on ACT-R architecture that emulates trainee performance. In this paper, we present insights gained from ACT-R modeling which, in turn, will be used to develop a VACR smart tutor.
Keywords: Visual aircraft recognition; Smart tutor; ACT-R models; Dynamic Bayesian networks; Intelligent tutoring systems
Augmenting Instructional Practice in GIFT Using the Engine for Management of Adaptive Pedagogy (EMAP) BIBAKFull-Text 595-604
  Benjamin Goldberg
Authoring adaptation in the Generalized Intelligent Framework for Tutoring (GIFT) is dependent on the functions made available in the pedagogical module. The Engine for Management of Adaptive Pedagogy (eMAP) has been constructed as an instructional management framework that guides pedagogical authoring and implementation within GIFT. The eMAP is structured around David Merrill's Component Display Theory (CDT) and is designed to support adaptive instruction based on the tenets of knowledge and skill acquisition. The framework is designed to assist with two facets of lesson creation. First, it is designed to serve as a guiding template for Subject Matter Experts when constructing intelligent and adaptive course materials that adhere to sound instructional design principles. And second, it serves as a framework to support instructional strategy focused research to examine pedagogical practices and the influence of individual differences on learning outcomes. In this chapter we will describe the fundamental components that make up the eMAP, followed by the authoring workflow associated with its implementation as described above. This includes an overview of the dependencies associated with the eMAP, which runs on relevant data stored in the learner model informing content selection and metadata used to describe course materials and pedagogical practices.
Keywords: Intelligent tutoring systems; Adaptive pedagogy; Instructional management; Individual differences; Personalized instruction
Measuring Concentration While Programming with Low-Cost BCI Devices: Differences Between Debugging and Creativity Tasks BIBAKFull-Text 605-615
  Víctor M. González; Romain Robbes; Gabriela Góngora; Salvador Medina
Computing devices have become a primary working tool for many professional roles, among them software programmers. In order to enable a more productive interaction between computers and humans for programming purposes it is important to acquire an awareness of human attention/concentration levels. In this work we report on a controlled experiment to determine if a low-cost BCI (Brain Computer Interface) device is capable of classifying whether a user is fully concentrated while programming, during three typical tasks: creativity (writing code), systematic (documenting the code) and debugging (improving or modifying the code to make it work). This study employs EEG (Electroencephalogram) signals, to measure an individual's concentration levels. The chosen BCI device is NeuroSky's Mindwave due to its availability in the market and low cost. The three tasks described are performed in a physical and digital form. A statistically significant difference between debugging and creativity tasks is revealed in our experiments, in both physical and digital tests. This is a good lead for following experiments to focus on these two areas. Systematic tasks might not bring good results due to their nature.
Keywords: BCI; EEG; Concentration levels; Programming tasks; Debugging; Creativity; Systematic
Adapting Immersive Training Environments to Develop Squad Resilience Skills BIBAKFull-Text 616-627
  Joan H. Johnston; Samantha Napier; William A. Ross
The United States Army defines readiness and resilience as tactically proficient Soldiers and highly adaptive problem solvers capable of overcoming challenges and making decisions with strategic consequences in ambiguous situations. To address the resilience training gap, the Squad Overmatch study produced recommendations for employing immersive and live training strategies within the Stress Exposure Training (SET) framework. SET is a three-phase training method designed to provide information, skills training, and practice; with the goal of learning how to cope and perform while exposed to combat stressors. The potential for a wide range of Soldier experience levels in the pre-deployment training phase requires structuring and facilitating immersive and live training to develop resilience skills. In this paper we provide recommendations for adapting immersive environments to focus on assessing unit "readiness to train," and employing methods and tools that improve training effectiveness.
Keywords: Stress exposure training; Resilience; Immersive; Battlefield; Squad Overmatch
Authoring Intelligent Tutoring Systems Using Human Computation: Designing for Intrinsic Motivation BIBAKFull-Text 628-639
  Andrew M. Olney; Whitney L. Cade
This paper proposes a methodology for authoring of intelligent tutoring systems using human computation. The methodology embeds authoring tasks in existing educational tasks to avoid the need for monetary authoring incentives. Because not all educational tasks are equally motivating, there is a tension between designing the human computation task to be optimally efficient in the short term and optimally motivating to foster participation in the long term. In order to enhance intrinsic motivation for participation, the methodology proposes designing the interaction to promote user autonomy, competence, and relatedness as defined by Self-Determination Theory. This design has implications for learning during authoring.
Keywords: Authoring; Intelligent tutoring system; Human computation; Motivation
Opportunities and Risks for Game-Inspired Design of Adaptive Instructional Systems BIBAKFull-Text 640-651
  Scott Ososky
The application of game elements within learning environments takes many forms, including serious games, interactive virtual environments, and the application of game mechanics within non-gaming contexts. Given the breadth of strategies for implementation game-elements into instructional systems, it is important to recognize that each strategy carries its own potential benefits and risks. The purpose of the current paper is to review the relevant interdisciplinary literature regarding the application of games and game-elements to learning contexts, and identify the factors to consider when developing a game-inspired instructional system. Secondly, the current discussion considers the special case of game technology and game design elements in intelligent tutoring, and identifies future research opportunities to meaningfully integrate such features in adaptive tutoring systems.
Keywords: Game-based learning; Intelligent tutoring systems; Adaptive tutoring; Gamification; Mental models; Motivation; Tutor-user interface
From Desktop to Cloud: Collaborative Authoring for Intelligent Tutoring BIBAKFull-Text 652-662
  Charlie Ragusa
Authoring of computer-based instruction employing intelligent tutoring (IT) presents many challenges. Chief among them is that for non-trivial domains, the knowledge and skills required to author maximally effective instruction often do not reside in a single individual. More often the best outcome is achieved by collaboration among some combination of instructional designers, subject matter experts, psychologists, traditional educators, and in some cases, software engineers. To meet this challenge, well designed collaborative authoring systems are needed. Cloud computing technologies, such as Platform as a Service (PaaS) and Infrastructure as a Service (IaaS), offer new possibilities for the construction of distributed authoring systems. In this paper we discuss several high-level design considerations for developing collaborative IT authoring systems, focusing on extending the capabilities of the existing Generalized Intelligent Framework for Tutoring (GIFT).
Keywords: Collaborative authoring; Intelligent Tutoring Systems; Cloud computing
Designing Representations and Support for Metacognition in the Generalized Intelligent Framework for Tutoring BIBAKFull-Text 663-674
  James R. Segedy; John S. Kinnebrew; Benjamin S. Goldberg; Robert A. Sottilare; Gautam Biswas
An important component of metacognition relates to the understanding and use of strategies. Thus, measuring and supporting students' strategy understanding in complex open-ended learning environments is an important challenge. However, measuring students' strategy use and understanding is a difficult undertaking. In this paper, we present our design for representing and supporting students in their understanding of strategies while working in complex, open-ended learning environments using the Generalized Intelligent Framework for Tutoring (GIFT). Our approach utilizes a wealth of previous research and relies on three primary instructional interventions: contextualized conversational assessments and feedback; reviewing knowledge and strategies; and teaching through analogies. We believe that incorporating these approaches into GIFT will allow for powerful instruction of complex tasks and topics.
Keywords: Metacognition; Strategy instruction; Feedback; Open-ended learning environment
A Personalized GIFT: Recommendations for Authoring Personalization in the Generalized Intelligent Framework for Tutoring BIBAFull-Text 675-682
  Anne M. Sinatra
Personalization of learning content can have a positive impact on learning in a computer based environment. Personalization can occur in a number of different ways, such as including an individual's name or entered content throughout the learning materials, or selecting examples based on self-reported preferences. The Generalized Intelligent Framework for Tutoring (GIFT) is an open-source, domain independent intelligent tutoring system framework. GIFT includes a number of different authoring tools (e.g., GIFT Authoring Tool, Survey Authoring System) that can be used to generate adaptive courses. In its current form, GIFT does not have specific mechanisms to support personalization of materials to the individual user based on pre-entered preferences. The current paper describes ways that personalization research has previously been conducted with GIFT. The paper additionally provides recommendations on new features that could be added to GIFT's authoring tools in order to support personalizing learning materials, guidance, and surveys that are provided to the learner.
Augmented Cognition on the Run: Considerations for the Design and Authoring of Mobile Tutoring Systems BIBAKFull-Text 683-689
  Robert A. Sottilare
This paper discusses considerations for design and authoring of mobile intelligent tutoring system (ITSs). ITSs are on the rise as tools for desktop tutoring of cognitive tasks (e.g., problem solving and decision making). To become truly ubiquitous, ITSs will be required to leave the desktop and support interactive, adaptive instruction on-the-move via mobile devices. We examined the capabilities of Google Glass as a potential hands-free platform to support mobile tutoring and found many of the functions serviceable as proxies to desktop tutoring functions. The potential of mobile platforms like Google Glass integrated with the Generalized Intelligent Framework for Tutoring (GIFT) provides a practical example on which to discuss limitations and project future capabilities for mobile tutoring.
Keywords: Intelligent tutoring systems; Mobile learning; Distributed learning; Mobile tutoring
Modeling Shared States for Adaptive Instruction BIBAKFull-Text 690-696
  Robert A. Sottilare
This paper discusses methods in which adaptive instructional techniques, strategies and tactics (collectively referred to henceforth as adaptive instruction) might be applied in a multi-learner or team training domain where accurate shared models of cognition and affect are critical to optimizing team performance, and individual learning, retention, and transfer. Application of these models in the Generalized Intelligent Framework for Tutoring (GIFT) is also discussed.
Keywords: Adaptive instruction; Intelligent tutoring systems; Adaptive tutoring; Team modeling; Unit modeling; Shared modeling
EEG Coherence Within Tutoring Dyads: A Novel Approach for Pedagogical Efficiency BIBAKFull-Text 697-706
  Bradly Stone; Kelly Correa; Nandan Thor; Robin Johnson
The current study examined EEG coherence across Coach-Learner dyads on a spatial reasoning video game, Tetris®, using an event-locked psychophysiological synching platform. We hypothesized that (1) an intra-individual increase in Theta and a decrease in high Alpha (10-12 Hz) fronto-temporal coherence would occur across increasing difficulty levels, and (2) inter-individual fronto-temporal coherence in high Alpha would increase among lower skilled players. A sample of n=5 healthy dyads completed the protocol with each learner playing 3 rounds of Tetris®. Across all participants (low-skilled and high-skilled), the intra-individual preliminary results presented herein indicate significant elevation in fronto-parietal coherence. Moreover, the low-skilled players experienced an increase in Theta coherence and high Alpha coherence -- the latter not as expected from literature. The high-skilled players had significant reductions in fronto-parietal high Alpha coherence and small increases in Theta. The inter-individual (coach-learner) dyadic coherence results for the low-skilled player showed increased Theta coherence for Coach-Frontal:Learner-Parietal (CF:LP), with no significant change in high Alpha. Meanwhile, an increase in high Alpha coherence was observed in the Coach-Parietal:Learner-Frontal (CP:LF). The high-skilled player experienced decreased Theta coherence for CF:LP, with no significant change in high Alpha, yet a substantial increase in Theta coherence and decrease in high Alpha coherence was observed for CP:LF. These data support the application of coherence analyses for the improvement of pedagogical approaches and provide optimism that further granulated explorations of the data herein could lead to a more thorough understanding of the dynamics of dyadic learning.
Keywords: EEG; Coherence; Dyads; Education; STEM

Applications of Augmented Cognition

Contact Activity Visualization for Seniors BIBAKFull-Text 709-721
  Ana Almeida; Micael Carreira; Joaquim Jorge; Daniel Gonçalves
Over the years, people raise their children and watch them as they make their adult lives away from home. Because of that, seniors lose contact and intimacy with their loved ones, as physical presence isn't as possible as desirable. Also, because of physical impairments that may arrive as years pass by, seniors may experience difficulties in communicating and interacting. Thus, a research project called PAELife (Personal Assistant for the Elderly Life) was created with the aim of fighting isolation and exclusion. Our personal contribution to this project is displaying the most active contacts in a visual, powerful way so that they notice which friends are contacting them more and which ones don't contact in a long time. To achieve that, we built a set of prototypes that display contacts' activity from different sources (email, social networks, etc.) and performed two user tests, in order to identify the best alternatives and understand if the senior citizens can correctly perceive the contacts' activity. The tests' feedback allowed us to know what prototypes to choose and the ones to discard. After analyzing the results we implemented a final functional prototype that matched all the requirements collected from the users.
Keywords: Social networks; Contacts; Activity; Senior citizens; Communication
Setting a Privacy and Security Comfort Zone in the Internet of Things BIBAKFull-Text 722-734
  Barbara Endicott-Popovsky; Scott David; Martha E. Crosby
This paper seeks to raise awareness of the potential benefits and detriments resulting from sensor intrusion in the Internet of Things (IoT). The conclusion of this paper is that the IoT has been rendered inevitable as the result of a confluence of historical trends, but that we can make choices regarding its fundamental architecture that can tip the balance of harm and benefit more toward individual or institutional rights and obligations. Once the choices are "baked in" they will be more difficult to alter in future IoT iterations. It is hoped that collective attention to the issues raised in this paper will help to guide these decisions so that the IoT systems we build will result in fewer surprises.
Keywords: Internet of things; Information on top; Insight on time
Designing, Developing, and Validating an Adaptive Visual Search Training Platform BIBAFull-Text 735-744
  Kelly S. Hale; Katie Del Giudice; Jesse Flint; Darren P. Wilson; Katherine Muse; Bonnie Kudrick
Transportation Security Officers (TSOs) are at the forefront of our nation's security, and are tasked with screening every bag boarding a commercial aircraft within the United States. TSOs undergo extensive classroom and simulation-based visual search training to learn how to identify threats within X-ray imagery. Integration of eye tracking technology into simulation-based training could further enhance training by providing in-process measures of traditionally "unobservable" visual search performance. This paper outlines the research and development approach taken to create an innovative training solution for X-ray image threat detection and resolution utilizing advances in eye tracking measurement and training science that provides individualized performance feedback to optimize training effectiveness and efficiency.
An Object-Centric Paradigm for Robot Programming by Demonstration BIBAKFull-Text 745-756
  Di-Wei Huang; Garrett E. Katz; Joshua D. Langsfeld; Hyuk Oh; Rodolphe J. Gentili; James A. Reggia
In robot programming by demonstration, we hypothesize that in a class of procedural tasks where the end goal primarily consists of the states of objects that are external to a task performer, one can significantly reduce complexity of a robot learner by not processing a human demonstrator's motions at all. In this class of tasks, object behaviors are far more critical than human behaviors. Based on this virtual demonstrator hypothesis, this paper presents a paradigm where a human demonstrates an object manipulation task in a simulated world without any of the human demonstrator's body parts being sensed by a robot learner. Based on the object movements alone, the robot learns to perform the same task in the physical world. These results provide strong support for the virtual demonstrator hypothesis.
Keywords: Programming by demonstration; Imitation learning; Human-robot interactions
Optimization-Based Training in ATM BIBAKFull-Text 757-766
  Amela Karahasanovic; Tomas Eric Nordlander; Patrick Schittekat
Air Traffic Management is responsible for guiding airplanes as efficiently and safely as possible at and between airports. A team of air traffic controllers is required to make good decisions at all times, even under high stress. The complexity of their tasks requires frequent and high-quality training to ensure constant high performance of the team. In this paper, we present work in progress on a novel training tool based on the Optimization-based Virtual Instructor. The tool we propose combines mathematical optimization with visualization, and is expected to improve the training quality while reducing the training cost. We discuss the new Virtual Instructor concept and introduce the necessary state-of-the-art advances needed for both visualization and mathematical optimization to make it work. Two early-stage visualization prototypes are presented. The paper concludes with a possible way forward in the development of the Virtual Instructor.
Keywords: ATM; Training; Optimization
Human Factors Within the Transportation Security Administration: Optimizing Performance Through Human Factors Assessments BIBAKFull-Text 767-776
  Bonnie Kudrick; Daniel Caggiano; Ann Speed
The human factors team in the Mission Analysis Division of TSA's Office of Security Capabilities explores the impact of technology, policies, procedures, and training on human systems performance during transportation security operations. This paper highlights some of the most critical human factors challenges currently facing the aviation security community and provides an overview of innovative on-going human factors projects at TSA that will address some of these challenges by enhancing performance assessment capabilities, improving training opportunities, and optimizing duty rotations and assignments.
Keywords: Aviation; Transportation; Security; Cognition; Workload; Vigilance; Attention; Visual search; Decision making; Personality; Aptitudes; Behavior detection; Image analysis; Training; Human performance; Human factors
Breathing Life into CPR Training BIBAKFull-Text 777-783
  Dominic Lamboy; Patricia J. Donohue
This study reports on our development and prototyping of an accessible, simplified simulation for teaching CPR in classrooms. The prototype involves an inexpensive digitally enhanced dummy that can be constructed from common available materials linked with an iPad or tablet running a customized program. The mobile program targets students at 5th grade and above and faculty for CPR training. iPad sensors register pressure manipulation on the dummy and the program responds with interactive instruction. Several tests with older youth and adults proved the simulation was effective in teaching simple CPR techniques that testers could remember the following week. With an improved dummy, we will conduct empirical tests across different age groups in the coming year.
Keywords: Physical cognition; Game theory; Simulation; Mobile learning
Enhanced Physical Security Through a Command-Intent Driven Multi-agent Sensor Network BIBAKFull-Text 784-795
  Joshua Love; Wendy Amai; Timothy Blada; Charles Little; Jason Neely; Stephen Buerger
Sandia's Intelligent Systems, Robotics, and Cybernetics group (ISRC) created the Sandia Architecture for Heterogeneous Unmanned System Control (SAHUC) to demonstrate how heterogeneous multi-agent teams could be used for tactical operations including the protection of high-consequence sites. Advances in multi-agent autonomy and unmanned systems have provided revolutionary new capabilities that can be leveraged for physical security applications. SAHUC applies these capabilities to produce a command-intent driven, autonomously adapting, multi-agent mobile sensor network. This network could enhance the security of high-consequence sites; it can be quickly and intuitively re-tasked to rapidly adapt to changing security conditions.
   The SAHUC architecture, GUI, autonomy layers, and implementation are explored. Results from experiments and a demonstration are also discussed.
Keywords: Command intent; Physical security; Heterogeneous; Multi-agent distributed; Hierarchical control; SAHUC
Technology-Supported Health Measures and Goal-Tracking for Older Adults in Everyday Living BIBAKFull-Text 796-806
  Blaine Reeder; Angela Richard; Martha E. Crosby
In this paper, we review in-home technologies for use by older adults and the potential for technology-supported health measures to support independent living by connecting older adults, informal caregivers, and health care providers. We outline areas for new research that include platforms for technology integration, software for integrated data analytics, design for usability, and patient goal elicitation. Within this research agenda, meaningful health measurements must be defined, stakeholder interactions must be understood, and technologies must be standardized to enable large-scale community-based field studies beyond small-scale feasibility studies.
Keywords: Sensors; Independent living; Older adults; Home care; Heart failure
The Use of Eye Tracking in Software Development BIBAKFull-Text 807-816
  Bonita Sharif; Timothy Shaffer
Eye trackers have been routinely used in psychology reading experiments and in website usability studies for many years. However, it is only recently that they have been used by more researchers in the software engineering community. In this paper, we categorize two broad areas in which eye tracking technology can benefit software development in a practical way. The first area includes using the eye tracker as an assessment tool for software artifacts, tools, and techniques. The second area deals with using eye tracking data from developers to inform certain software tools and software development tasks such as providing developer recommendations and software traceability tasks. Examples of experiments and studies done in each of these broad areas is presented and discussed along with future work. The results point towards many benefits that eye trackers provide to augment the daily lives of programmers during software development.
Keywords: Eye tracking; Software development; Software traceability; Assessing software artifacts; Program comprehension
An Examination of Visual Search Success for Transportation Security Officers and Behavior Detection Officers BIBAKFull-Text 817-824
  Randall D. Spain; Jerry W. Hedge; Katrina M. Ladd
This paper discusses ongoing research that seeks to better understand the core visual search skills and requirements of Transportation Security Officers (TSOs) and Behavior Detection Officers (BDOs). The purpose of the first phase of research is to compare TSO and BDO visual search performance on a simple visual search task and to determine whether certain personality and demographic characteristics are related to search performance. The goal of the second phase of research is to identify measures and assessment devices that are more applicable to the visual search requirements of the BDO position. Methods and approaches used to answer key questions related to each phase of research are described, as are potential implications of the research.
Keywords: Visual search; Human performance; Individual differences; Assessments
Determining the Optimal Time on X-Ray Analysis for Transportation Security Officers BIBAKFull-Text 825-834
  Ann Speed; Austin Silva; Derek Trumbo; David Stracuzzi; Christina Warrender; Michael Trumbo; Kristin Divis
The Transportation Security Administration has a large workforce of Transportation Security Officers, most of whom perform interrogation of x-ray images at the passenger checkpoint. To date, TSOs on the x-ray have been limited to a 30-min session at a time, however, it is unclear where this limit originated. The current paper outlines methods for empirically determining if that 30-min duty cycle is optimal and if there are differences between individual TSOs. This work can inform scheduling TSOs at the checkpoint and can also inform whether TSOs should continue to be cross-trained (i.e., performing all 6 checkpoint duties) or whether specialization makes more sense.
Keywords: Visual search; Fatigue; Vigilance; Transportation security agency