Empirical Analysis of EEG and ERPs for Psychophysiological Adaptive Task Allocation

摘要

The present study was designed to test the efficacy of using Electroencephalogram (EEG) and Event-Related Potentials (ERPs) for making task allocation decisions. Thirty-six participants were randomly assigned to an experimental, yoked, or control group condition. Under the experimental condition, a tracking task was switched between task modes based upon the participant's EEG. The results showed that the use of adaptive aiding improved performance and lowered subjective workload under negative feedback as predicted. Additionally, participants in the adaptive group had significantly lower RMSE and NASA-TLX ratings than participants in either the yoked or control group conditions. Furthermore, the amplitudes of the N1 and P3 ERP components were significantly larger under the experimental group condition than under either the yoked or control group conditions. These results are discussed in terms of the implications for adaptive automation design.