A Psychophysiological and Performance Based Prediction System for Adaptive Aiding

As military equipment becomes more sophisticated and complex, missions become significantly more cognitively demanding. In order to achieve the objective of preventing errors and reducing cognitive demands on military personnel, a system is needed that is able to assess and predict operator stress, attention and overload states and provide adaptive aiding to maintain the operator in a state of maximal situation awareness and response readiness. Intelligent Automation, Inc. (IAI) proposes to develop an adaptive aiding system that uses a combination of performance and situational awareness assessments to tune the sensor integration algorithm to detect expected future states of cognitive overload, high levels of stress, and high and low levels of task-focused attention. The system will be based on three wearable devices that contain a total of nine wireless psychophysiological sensors. This project focuses on three key aspects of the system design: 1) comparing the efficiency and utility of Fisher Discriminant Analysis and artificial neural networks for integrating sensor data; 2) comparing two operator modeling systems (dynamic event-triggered pattern analysis and the Dynamic Integration Diagram) for predicting operator functional state based on psychophysiological, performance and environmental data; and 3) designing an adaptive aiding interface for assisting operators prior to cognitive overload.