EOG metrics for cognitive workload detection

Abstract Increasing workload is a central notion in human factors research that can decrease the performance and yield accidents. Thus, it is crucial to understand the impact of different internal operator’s factors including eye movements, memory and audio-visual integration. Here, we explored the relationship between cognitive workload (low vs. high) and eye movements (saccades, fixations and smooth pursuit). The task difficulty was induced by auditory noise, arithmetical count and working memory load. We estimated cognitive workload using EOG and EEG-based mental state monitoring. One novelty consists in recording the EOG around the ears (alternative EOG) and around the eyes (conventional EOG). The number of blinks and saccades amplitude increased along with the difficulty increase (p ≤ 0.05). We found significant correlations between EOG and EEG (theta/alpha ratio) and between conventional and alternative EOG signal. The increase in cognitive load may disturb the coding and maintenance of related visual information. Alternative EOG metrics could be a valuable tool for detecting workload.