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System to Evaluate and Assess Holistic Aircrew Workload (SEAHAWK)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-16-C-0227
Agency Tracking Number: N16A-002-0027
Amount: $79,998.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N16A-T002
Solicitation Number: 2016.0
Solicitation Year: 2016
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-05-11
Award End Date (Contract End Date): 2016-12-19
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Dr. Bethany Bracken
 (617) 491-3474
Business Contact
 Mark Felix
Phone: (617) 491-3474
Research Institution
 George Mason University
 Dr. Tyler Shaw
Prince William Campus 10900 University Blvd MSN 5B3
Manassas, VA 20110
United States

 (703) 993-5387
 Nonprofit College or University

The Navy is continually developing new technologies to improve warfighting effectiveness. These technologies risk overloading Aircrews physical and cognitive capacities, thereby degrading performance. To mitigate that risk, the Navy needs a system to assess Aircrews physical and cognitive workloads unobtrusively and objectively. Such a system must (1) perform real-time data collection in a robust and unobtrusive fashion; (2) extract, fuse, and process indicators of physical and cognitive workload; (3) predict performance changes due to the development of expertise among Aircrew; (4) characterize workload at individual, team, and multi-team (system) levels; and (5) display results in a way that supports the information requirements of the users. To meet these requirements Charles River Analytics proposes to design and demonstrate a System to Evaluate and Assess Holistic Aircrew Workload (SEAHAWK). In Phase I, we will deliver a prototype SEAHAWK system that includes: (1) a Sensor Suite, including forehead and peripheral (i.e. arm band) sensors; (2) algorithms to extract, process, and fuse sensor data; (3) algorithms to interpret these data and output assessments of individual and team workload; (4) algorithms to extrapolate the effects of expertise advancement on workload; and (5) a user interface to present output in a format understandable to users.

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

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