Augmented Cognition for Tactical Tomahawk Weapon Control System Operators

Twelve individuals took part in an experiment which investigated the feasibility of using physiological sensors to apply a pacing mitigation strategy to help prevent cognitive-overload-induced performance declines. The participants performed tasks using a simulated Tactical Tomahawk Weapons Control System (TTWCS) while wearing electroencephalograph (EEG), electrocardiograph (EKG), and galvanic skin response (GSR) sensors. The tasks, retargeting missiles in response to emergent targets and responding to alerts in the form of questions about the ongoing strike, were performed in the context of low, medium, and high workload scenarios. In the control condition, data from the sensors were collected, but not used to influence task presentation. In the experimental condition, the collected data were used to apply the pacing mitigation—that is, to determine the appropriate times to present the interrupting alert tasks. Analysis revealed that using sensor data to influence task presentation led to a 66.8% reduction in the number of erroneous responses to alerts, a 34.6% decrease in decision making time for low workload scenarios and an overall reduction in decision making time of 20.4%, and a 25.5% increase in the number of missiles that participants could handle simultaneously. These results indicate that human performance may be improved by monitoring physiological responses and intervening before cognitive overload can cause performance degradation. This research effort is relevant to future TTWCS development because the cognitive workload demands placed on TTWCS operators are expected to increase as new capabilities of Tomahawk missiles are introduced and because military reduced manning initiatives will continue to require that job functions be performed by fewer personnel. However, before the technology which was tested during this experiment could be deployed in an operational environment, physiological sensors must become more comfortable, accurate and mobile and less sensitive to inter-individual variation. Furthermore, more detailed task analyses are needed to identify the specific task components within the TTWCS environment that will yield the greatest performance gain. This effort, combined with other additional research, could yield performance improvements in the operational environment that exceed those observed during the laboratory-based experiment reported here.