Аңдатпа
The resource model of vigilance (Warm, Parasuraman, & Matthews, 2008) suggests that EEG-based indices of workload might be used to monitor the operator’s fitness to sustain signal detection. 92 participants performed a 40 minute vigilance task believed to be sensitive to resource availability. Half performed in a cued condition, half without cues. Findings confirmed that cueing reduces workload and enhances vigilance. EEG was recorded throughout performance. Of the various EEG indices analyzed, lower frequency alpha and the Task Load Index (TLI) corresponded most closely to changes in signal detection rates. Other indices, the Engagement Index (EI) and frontal theta, did not show systematic decrement but discriminated cued and uncued conditions towards the end of the task. Implications of the findings for using EEG to drive adaptive automation are discussed.