Objective: The Electroencephalogram (EEG) is gaining popularity as a physiological measure for neuroergonomics in human factor studies because it is objective, less prone to bias, and capable of assessing the dynamics of cognitive states. This study investigated the associations between memory workload and EEG during participants' typical office tasks on a single-monitor and dual-monitor arrangement. We expect a higher memory workload for the single-monitor arrangement. Approach: We designed an experiment that mimics the scenario of a subject performing some office work and examined whether the subjects experienced various levels of memory workload in two different office setups: 1) a single-monitor setup and 2) a dual-monitor setup. We used EEG band power, mutual information, and coherence as features to train machine learning models to classify high versus low memory workload states. Main results: The study results showed that these characteristics exhibited significant differences that were consistent across all participants. We also verified the robustness and consistency of these EEG signatures in a different data set collected during a Sternberg task in a prior study. Significance: The study found the EEG correlates of memory workload across individuals, demonstrating the effectiveness of using EEG analysis in conducting real-world neuroergonomic studies.

翻译：摘要：目的：脑电图（EEG）作为人因工程研究中神经工效学的一种生理测量指标正日益受到重视，因其具有客观性、不易受偏差影响，并能评估认知状态的动态变化。本研究探讨了在单显示器与双显示器配置下，参与者执行典型办公室任务时记忆工作负荷与EEG之间的关联。我们预期单显示器配置会产生更高的记忆工作负荷。方法：我们设计了一项模拟受试者执行办公室工作的实验，并考察了受试者在两种不同办公设置（1）单显示器设置和2）双显示器设置）中是否经历了不同水平的记忆工作负荷。我们采用EEG频带功率、互信息和相干性作为特征，训练机器学习模型以区分高记忆工作负荷状态与低记忆工作负荷状态。主要结果：研究结果表明，这些特征展现出所有参与者间一致的显著差异。我们还在先前研究中通过斯特恩伯格任务收集的另一数据集上验证了这些EEG特征的稳健性和一致性。意义：研究发现了个体间记忆工作负荷的EEG相关指标，证明了在真实场景神经工效学研究中运用EEG分析的有效性。