Thursday, 21 July 2016 |
08:00 – 10:00 |
S085: Enhance Human Performance in Augmented Training Environments: Measurements and Models Room: Pier 9 Chair(s): Samantha Napier, Debra Patton, U.S. Army Research Laboratory, United States
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- Exploring the Hybrid Space: Theoretical Framework Applying Cognitive Science in Military Cyberspace Operations
Øyvind Jøsok, Norwegian Cyber Defense Academy, Norway; Benjamin J. Knox, Kirsi Helkala, Norwegian Defence Cyber Academy, Norway; Ricardo G. Lugo, Lillehammer University College, United States; Stefan Sütterlin, Lillehammer University College, Norway; Paul Ward, Huddersfield University, United Kingdom
- [Presentation Canceled] Training Tactical Combat Casualty Care with an Integrated Training Approach
Lisa Townsend, Laura Milham, Dawn Riddle, Henry Phillips, Naval Air Warfare Center Training Systems Division (NAWCTSD), United States; Joan H. Johnston, U.S. Army Research Laboratory, United States; William A. Ross, Cognitive Performance Group, Inc., United States
- Alternate Rubric for Performance Assessment of Infantry Soldier Skills Training
Douglas B. Maxwell, U.S. Army Research Laboratory, United States; Jonathan A. Stevens, Crystal S. Maraj, University of Central Florida, United States
- Physiological Measures of Arousal during Soldier-Relevant Tasks Performed in a Simulated Environment
Debra Patton, Katherine Gamble, U.S. Army Research Laboratory, United States
- Using an Augmented Training Event to Collect Data for Future Modeling Purposes
Samantha Napier, Christopher Best, Debra Patton, U.S. Army Research Laboratory, United States; Glenn Hodges, Training and Doctrine Command
Army Capabilities Integration Center, United States
- The Role of Simulation in Designing Human-Automation Systems
Christina F. Rusnock, Jayson G. Boubin, Joseph J. Giametta, Tyler J. Goodman, Anthony J. Hillesheim, Sungbin Kim, David R. Meyer, Michael E. Watson, Air Force Institute of Technology, United States
- Making Sense of Cognitive Performance in Small Unit Training
William A. Ross, Cognitive Performance Group, Inc., United States; Joan H. Johnston, U.S. Army Research Laboratory, United States; Dawn Riddle, Henry Phillips, Lisa Townsend, Laura Milham, Naval Air Warfare Center Training Systems Division (NAWCTSD), United States
- Measuring Stress in an Augmented Training Environment: Approaches and Applications
David L. Jones, Quantified Design Solutions, United States; Sara Dechmerowski, Design Interactive, Inc., United States
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S086: Designing and Implementing Augmented Reality Room: Pier 8 Chair(s): Tess Bailie, Carnegie Mellon University / Draper, United States
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- User Abilities in Detecting Vibrotactile Signals on the Feet Under Varying Attention Loads
Alison Gibson, Massachusetts Institute of Technology (MIT), United States; Andrea K. Webb, Draper Laboratory, United States; Leia Stirling, Massachusetts Institute of Technology (MIT), United States
- A Systems Approach for Augmented Reality Design
Andrea K. Webb, Emily C. Vincent, Pooja Patnaik, Jana L. Schwartz, Draper Laboratory, United States
- The Willful Marionette: Modeling Social Cognition Using Gesture-Gesture Interaction Dialogue
Mohammad Mahzoon, UNC Charlotte, United States; Mary Lou Maher, University of North Carolina at Charlotte, United States; Kazjon Grace, Lilla LoCurto, Bill Outcault, UNC Charlotte, United States
- Measuring the Effect of Tangible Interaction on Design Cognition
Mary Lou Maher, John Gero, Lina Lee, University of North Carolina at Charlotte, United States; Rongrong Yu, University of Newcastle, Australia; Tim Clausner, University of Maryland, United States
- Implementing User-Centered Methods and Virtual Reality to Rapidly Prototype Augmented Reality Tools for Firefighters
Tess Bailie, James Martin, Carnegie Mellon University / Draper, United States; Zachary Aman, Ryan Brill, Alan Herman, Carnegie Mellon University, United States
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10:30 – 12:30 |
S106: Closed-Loop Systems: Best Practices for Standardizing, Attribute Selection, and Modeling Room: Pier 9 Chair(s): Lauren Reinerman-Jones, Ryan W. Wohleber, University of Central Florida, United States
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- Psychological Baseline Methods and Usage
Avonie Parchment, Ryan W. Wohleber, Lauren Reinerman-Jones, University of Central Florida, United States
- Theoretical versus Mathematical Approach to Modeling Psychological and Physiological Data
Lauren Reinerman-Jones, University of Central Florida, United States; Stephanie J. Lackey, Design Interactive, Inc., United States; Julian Abich IV, Brandon Sollins, University of Central Florida, United States; Irwin Hudson, U.S. Army Research Laboratory, United States
- Augmenting Robot Behaviors Using Physiological Measures of Workload State
Grace Teo, Lauren Reinerman-Jones, Gerald Matthews, Daniel Barber, Jonathan Harris, University of Central Florida, United States; Irwin Hudson, U.S. Army Research Laboratory, United States
- Challenges Selecting Attributes for Developing Models of Physiological Data
Nelson Lerma, Naval Air Warfare Center Training Systems Division (NAWCTSD), United States; Lauren Reinerman-Jones, University of Central Florida, United States
- Considerations in Physiological Metric Selection for Online Detection of Operator State: A Case Study
Ryan W. Wohleber, Gerald Matthews, University of Central Florida, United States; Gregory J. Funke, Air Force Research Laboratory, United States; Jinchao Lin, University of Central Florida, United States
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13:30 – 15:30 |
S126: Machine Learning on Cognitive Data Room: Pier 9 Chair(s): Leanne Hirshfield, Syracuse University, United States
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- [Presentation Canceled] Using fNIRS for Realtime Cognitive Workload Assessment
Samuel W. Hincks, Tufts University, United States; Daniel Afergan, Google Inc., United States; Robert J.K. Jacob, Tufts University, United States
- Multi‐Model Approach to Human
Functional State Estimation
Kevin Durkee, Avinash Hiriyanna, Scott Pappada, John Feeney, Aptima, Inc., United States; Scott Galster, Air Force Research Laboratory, United States
- A More Complete Picture of Emotion using Electrocardiogram and Electrodermal Activity to Complement Cognitive Data
Danushka Bandara, Syracuse University, United States; Stephen Song, Syracuse University, Korea; Leanne Hirshfield, Senem Velipasalar, Syracuse University, United States
- Truthiness: Challenges associated with employing machine learning on neurophysiological sensor data
Mark Costa, Sarah Bratt, Syracuse University, United States
- Estimate Emotion Method to Use Biological, Symbolic Information Preliminary Experiment
Yuhei Ikeda, Yoshiko Okada, Midori Sugaya, Shibaura Institute of Technology, Japan
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16:00 – 18:00 |
S144: Toward Practical Brain-Computer Interfaces in Real Life Room: Pier 9 Chair(s): Yuan-Pin Lin, Tzyy-Ping Jung, University of California, San Diego, United States
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- Session-to-session transfer in detecting steady-state visual evoked potentials with individual training data
Masaki Nakanishi, University of California, San Diego, United States; Yijun Wang, Chinese Academy of Sciences, P.R. China; Tzyy-Ping Jung, University of California, San Diego, United States
- Augmenting VR/AR Applications with EEG/EOG Monitoring and Oculo-Vestibular Recoupling
John K. Zao, National Chiao Tung University, Taiwan; Tzyy-Ping Jung, University of California, San Diego, United States; Hung-Ming Chang, Tchin-Tze Gan, Cerebra Technologies, Taiwan; Yu-Te Wang, Yuan-Pin Lin, University of California, San Diego, United States; Wen-Hao Liu, Guang-Yu Zheng, National Chiao Tung University, Taiwan; Chin-Kuo Lin, Chia-Hung Lin, PowerForce Technologies, Taiwan; Yu-Yi Chien, Fang-Cheng Lin, Yi-Pai Huang, Sergio José Rodríguez Méndez, National Chiao Tung University, Taiwan; Felipe A. Medeiros, University of California, San Diego, United States
- Comparing EEG Artifact Detection Methods for Real-World BCI
Michael W. Nonte, DCS Corporation, United States; William D. Hairston, U.S. Army Research Laboratory, United States; Stephen M. Gordon, DCS Corporation, United States
- Exploring the EEG Correlates of Neurocognitive Lapse with Robust Principal Component Analysis
Chun-Shu Wei, Yuan-Pin Lin, Tzyy-Ping Jung, University of California, San Diego, United States
- Predicting EEG Sample Size Required for Classification Calibration
Zijing Mao, University of Texas at San Antonio, United States; Tzyy-Ping Jung, University of California, San Diego, United States; Chin-Teng Lin, National Chiao Tung University, Taiwan; Yufei Huang, University of Texas at San Antonio, United States
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