Assessing mental workload in virtual reality based EOT crane operations: A multi-measure approach

Background: Eye-movement metrics and subjective workload measures are extensively used to determine mental workload of participants. The aim of this study was to assess Electric overhead travelling (EOT) crane operators' mental workload variability based on eye movement metrics such as fixation frequency, fixation duration, saccade duration, saccade amplitude, and fixation/saccade ratio during EOT crane operations in virtual reality (VR) based EOT crane simulator. Methods: A 2(k) (k = 3) factorial experiment with factors namely, hazardous scenario, activity level, and trial was designed and conducted to demonstrate the proposed assessment approach. Throughout the experiment, we recorded the eye movements of 12 EOT crane operators of a steel industry of authors' country. Post experiment, the National Aeronautics and Space Administration task load index (NASA-TLX) was adopted as a subjective workload measure and run time of task completion was recorded. Eye-movement metrics, subjective workload measure, run time were tested with multivariate analysis of variance (MANOVA), and three way repeated measure analysis of variance (ANOVA). Results: At the level of alpha = 0.05, the experimental factors significantly influence the means of eye movement metrics, subjective ratings and run time. There was also significant influence among their interactions. A positive correlation was also found for eye movements metrics with NASA-TLX and run time. Conclusions: Eye movement metrics help in understanding the mental workload of participants unobtrusively and continuously. Analysis of subjective workload measure and run time along with eye-gaze analysis provide a deeper understanding on the pattern of mental workload.