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Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-19-P-6011
Agency Tracking Number: F18B-001-0052
Amount: $149,869.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF18B-T001
Solicitation Number: 18.B
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-01-03
Award End Date (Contract End Date): 2019-01-03
Small Business Information
3600 Green Court Suite 600
Ann Arbor, MI 48105
United States
DUNS: 009485124
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Caitlin Tenison
 Research Scientist
 (210) 288-2389
Business Contact
 Laura Schwennesen
Phone: (734) 887-7683
Research Institution
 Carnegie Mellon University
 Dr. John R. Anderson Dr. John R. Anderson
5000 Forbes Ave.
Pittsburgh, PA 15213
United States

 (412) 417-7008
 Nonprofit College or University

From individualized training, to responsive decision-support, and improved human-machine teaming, the ability to accurately predict the cognitive state of an individual in real time would open the door for numerous technologies that would benefit the operational needs of the warfighter. Until now, much of the research using EEG for operational needs has focused on tailoring a system to detect only a few cognitive states. This solution provides severely limited coverage of the space that this technology could be applied to, and is not a realistic path for developing neuroimaging as an operational asset. Soar Technology and Dr. John Anderson at Carnegie Mellon University propose the development of the CogTracer Toolkit. This toolkit supports the prediction and detection of cognitive states from electroencephalography (EEG) signals. The CogTracer toolkit will be integrated with the ACT-R cognitive architecture and use state-of-the-art machine learning approaches applied to neuroimaging data. Our Phase I work formalizes and extends the ongoing research of Dr. Anderson and colleagues for detecting cognitive states from neuroimaging data. Through research and validation, we will extend these methods to support a wide range of tasks, functional capabilities and EEG signal components.

* Information listed above is at the time of submission. *

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