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

Kathryn A. Feltman, Johnathan F. Vogl, Aaron McAtee, Amanda M. Kelley
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Abstract

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.
利用脑电图测量飞行员的工作量:个性化的工作量控制方法
测量操作员的生理状态并利用该数据预测未来的性能下降一直是许多运输领域的目标。在陆军航空兵方面,实现这一目标可以开发出适应操作员需求的自适应自动化系统。然而,要实现这一目标,需要使用与现实生活类似的实验场景,以便诱导出能够考虑到个体在经验、接触和对工作量操作的感知方面差异的相关状态。在本研究中,我们采用了一种个性化的方法来操纵工作负荷,以考虑个体对工作负荷操纵的反应差异,同时仍然提供与操作相关的飞行体验。第一次访问的目的是确定个人的工作量阈值,第二次访问则是进行个性化工作量操作的飞行。两次飞行都收集了脑电图数据,以及对工作量和飞行表现的主观评分。与低工作量飞行相比,高工作量飞行期间的主观评分更高(p < 0.001)。在脑电图方面,与高工作量情况相比,基线飞行情况下的额叶α(p = 0.04)和θ(p = 0.01)值较低,β/(α+θ)比率(p = 0.02)较高。个体化方法在脑电图和主观评价方面都表现出了更高的效应大小,这表明使用这种方法可以为飞行员产生高负荷工作提供更可靠的方法。
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