Task Difficulty in Virtual Reality Forklift Training Can Be Assessed Using Eeg Measurements

Abstract

Objective: We investigated the efficacy of NASA-Task Load Index (NASA-TLX) and Electroencephalographic (EEG) in measuring cognitive workload during Virtual Reality (VR)-based forklift driving. Particularly, we assessed their sensitivity to varying levels of task difficulty and repeated training as well as correlations between them.

Background: Sufficient training of forklift operators is crucial for their performance and safety. Though the benefits of VR-based forklift training are well recognized, there is a lack of comprehensive cognitive workload assessment among novice drivers in such training.

Methods: Twenty novice participants completed two sessions, each involving three forklift driving lessons at three difficulty levels, in a VR simulator. Perceived workload (NASA-TLX) and normalized EEG activity were employed to assess cognitive workload.

Results: Five of the six NASA-TLX subscales and EEG activity in all frequency bands significantly increased with increasing task difficulty. However, we did not observe significant changes in cognitive workload measured by EEG in the second training session. Perceived workload and EEG measures showed moderate, positive correlations.

Conclusion: Both NASA-TLX and EEG measures were sensitive to task difficulty levels. An additional training session did not result in significant change of workload for any of the EEG frequency bands. Therefore, more than two training sessions are needed to examine if repeated training can reduce the operator’s workload in VR.

Application: EEG measures appear to have utility in monitoring workload across various levels of forklift driving task difficulty. Thus, incorporating real-time monitoring of workload using EEG in VR forklift training could enhance the training process.

Keywords: Forklift operation, Virtual reality, Task difficulty, Electroencephalogram (EEG), Workload assessment