Unmanned systems operations are complex, cognitively demanding tasks that elicit highly variable workload. The ability to predict performance and workload within these complex tasks can provide a powerful tool for practitioners regarding fit-for-duty verification. Further, monitoring workload aids in diagnostic assessment of factors that impact performance. The goal for this analysis was to examine the quality of cross-task averages of both baseline and concurrent psychophysiological and subjective measures to predict task performance and perceived workload. At a theoretical level, these findings suggest the need for a multivariate conceptualization of processing ‘resources’, encompassing both implicit and explicit responses. At a practical level, both subjective and psychophysiological measures may be necessary for optimizing performance prediction, at least for certain tasks.
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