Abstract

Desmond and Hancock (2001) proposed that two types of cognitive fatigue can arise depending on the nature of a task: active or passive. The purpose of this study was to use electroencephalographic indices of task engagement and a candidate marker of strain to differentiate these two fatigue states. Participants ( N = 84) performed a generalized flight simulation task for 62 min under either active, passive, or control conditions. Passive fatigue was characterized by reduced EEG engagement and initially elevated and stable ratios of Fz theta to POz alpha power compared to active fatigue. No performance differences were found between the fatigue conditions; however, an overall speed-accuracy trade-off was observed from pre to post fatigue induction. These results support theoretical and empirical distinctions between active and passive fatigue and have potential applications for developing augmented cognition technologies to deliver appropriate fatigue countermeasures in automated operational environments.

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