Abstract
A bio-cybernetic, closed-loop system was validated for use in an adaptive automation environment. Subjects were asked to perform either a single task or multiple tasks from the Multi-Attribute Task Battery. EEG was continuously sampled while they performed the task(s) and an EEG index was derived (20 Beta/Alpha + Theta). The system switched between manual and automatic modes according to the level of operator engagement based upon the EEG index. The NASA-TLX was administered after each trial. The results of the study demonstrated that it was possible to moderate an operator's level of engagement through a closed-loop system driven by the operator's EEG. In addition, the system was sensitive to increases in task load. These findings show promise for designing adaptive automation technology around psychophysiological input.
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