The main goal of the present study was to examine the feasibility of employing event-related brain potentials to measure dynamic changes in mental workload. Subjects performed two tasks, monitoring and mental arithmetic, both separately and together. Following an analysis of the performance, subjective workload ratings, and average ERP data in the single-and dual-task conditions, two different conditions from each of the tasks were selected for further analysis. A bootstrapping approach was employed to determine the amount of ERP data required to discriminate between these conditions. The results of these analyses indicated that (a)90% correct discrimination could be achieved with from 1 to 11 s of ERP data, (b) the best ERP measures varied across tasks and subjects, and (c) the inclusion of temporal and spatial aspects of the ERP data improved the ability to discriminate among workload levels. The data is discussed with respect to real-time assessment of mental workload.
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