Integration of Psychophysiological and Performance Measures into an Adaptive Aiding System

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$99,710.00
Award Year:
2008
Program:
SBIR
Phase:
Phase I
Contract:
FA8650-08-M-6826
Agency Tracking Number:
F073-013-0743
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
DESIGN INTERACTIVE, INC.
1221 E. Broadway, Suite 110, Oviedo, FL, 32765
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
075104708
Principal Investigator:
Sven Fuchs
Senior Research Associate
(407) 706-0977
sven@designinteractive.net
Business Contact:
John Stanney
CFO
(407) 706-0977
john@designinteractive.net
Research Institution:
n/a
Abstract
To meet the challenges imposed on command-and-control environments by next-generation weapons systems and continued reduced manning efforts, we will develop the Proactive Aiding in Command and Control Environments System (PACES) - an automatic agent, informed by real-time data streams from the system, the mission, and the operator's cognitive state. PACES will use dynamic constraint-based task modeling to anticipate future mission state and operator functional state (OFS) ahead of time. An existing workload analysis method will be used to calculate expected operator load for the future task demands anticipated by the model in real-time. Given this information, preventive adaptations of the information display can be dynamically applied to avoid cognitive bottlenecks before they occur. In addition to preventive adaptation, PACES will employ physiological measures, specifically electroencephalogram and eye tracking, to assess the operator's actual cognitive state and mitigate problems in real-time. Physiological measures will provide input to an intelligent Soar architecture to derive OFS indicators and inform PACES when adaptive aiding is needed. The model may further analyze workflow history and operator's physiological and behavioral responses to system events in order to dynamically adjust and improve the predictive modeling component and mitigation strategies.

* information listed above is at the time of submission.

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