Measuring aviator workload using EEG: an individualized approach to workload manipulation

Measuring an operator's physiological state and using that data to predict future performance decrements has been an ongoing goal in many areas of transportation. Regarding Army aviation, the realization of such an endeavor could lead to the development of an adaptive automation system which adapts to the needs of the operator. However, reaching this end state requires the use of experimental scenarios similar to real-life settings in order to induce the state of interest that are able to account for individual differences in experience, exposure, and perception to workload manipulations. In the present study, we used an individualized approach to manipulating workload in order to account for individual differences in response to workload manipulations, while still providing an operationally relevant flight experience.

Eight Army aviators participated in the study, where they completed two visits to the laboratory. The first visit served the purpose of identifying individual workload thresholds, with the second visit resulting in flights with individualized workload manipulations. EEG data was collected throughout both flights, along with subjective ratings of workload and flight performance.

Both EEG data and workload ratings suggested a high workload. Subjective ratings were higher during the high workload flight compared to the low workload flight (p < 0.001). Regarding EEG, frontal alpha (p = 0.04) and theta (p = 0.01) values were lower and a ratio of beta/(alpha+theta) (p = 0.02) were higher in the baseline flight scenario compared to the high workload scenario. Furthermore, the data were compared to that collected in previous studies which used a group-based approach to manipulating workload.

The individualized method demonstrated higher effect sizes in both EEG and subjective ratings, suggesting the use of this method may provide a more reliable way of producing high workload in aviators.