Zahabi, Saman Jamshid NezhadIslam, Md ShafiqulKim, SunwookLau, NathanNussbaum, Maury A.Lim, Sol2025-04-152025-04-152025-050169-8141https://hdl.handle.net/10919/125200Virtual Reality (VR)-based training offers a safe and engaging environment for training forklift operators. Given the complexity of forklift operation, monitoring the cognitive workload of novice operators in these virtual settings is essential for optimizing the training process. This study investigated cognitive workload variation during a VR-based training for forklift operators due to varying levels of task difficulty and repeated training. Twenty novice participants completed two sessions in a VR simulator with each session including three forklift driving lessons at three difficulty levels. Perceived workload (NASA-TLX) and normalized encephalographic (EEG) activity were employed to assess cognitive workload. Five of the six NASA-TLX subscales and EEG activity in three distinct frequency bands (theta, alpha and beta) all significantly increased with increasing task difficulty. However, we did not observe significant changes in cognitive workload as measured by EEG in the second training session, highlighting a potential limitation in using EEG to track workload variations across days. Perceived workload and EEG measures showed moderate, positive correlations. Our results highlight the potential of EEG for real-time monitoring of workload during VR-based forklift training, particularly in differentiating tasks of varying difficulty. While more research is needed to confirm measurement consistency across sessions, this capability could facilitate worker monitoring to deliver timely alerts or assistance when workload levels exceed optimal thresholds.11 page(s)application/pdfenIn CopyrightForklift operationVirtual realityTask difficultyElectroencephalogram (EEG)Workload assessmentArticle - Refereedhttps://doi.org/10.1016/j.ergon.2025.103718107Nussbaum, Maury [0000-0002-1887-8431]Kim, Sun Wook [0000-0003-3624-1781]1872-8219