A Multimodal Approach Exploiting EEG to Investigate the Effects of VR Environment on Mental Workload

Mondellini, Marta; Pirovano, Ileana; Colombo, Vera; Arlati, Sara; Sacco, Marco; Rizzo, Giovanna; Mastropietro, Alfonso · 2023 · Crossref

DOI: 10.1080/10447318.2023.2258017

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Summary

This study investigates the impact of virtual reality (VR) immersion levels on mental workload (MWL) using a multimodal approach that combines subjective ratings, performance metrics, and electroencephalography (EEG). While VR is increasingly used in training and rehabilitation, its effect on cognitive load remains debated, with prior research showing conflicting results regarding whether immersion increases or decreases MWL. This research specifically addresses the gap in literature regarding the use of EEG to objectively assess MWL in VR environments compared to traditional desktop interfaces. The experimental design involved 27 healthy participants who performed an n-back cognitive task under two conditions: using a head-mounted display (HMD, HTC Vive Pro) for immersive VR and a desktop computer. The task consisted of four levels of increasing complexity, varying by the number of steps to remember (n=1 or n=2) and the modality of stimuli (visual only or visual and auditory). MWL was assessed subjectively using the NASA Task Load Index (NASA-TLX) after each task level. Objective measures included error rates (ERs) and reaction times (RTs). Physiological data were collected via a 32-channel EEG system, from which an MWL index (MWLI) was derived by calculating the ratio of theta power at the frontal midline (Fz) to alpha power at the parietal midline (Pz). Data were pre-processed using Independent Component Analysis and Artifact Subspace Reconstruction to remove noise. The results indicated that task complexity significantly affected all measures: higher difficulty levels led to increased subjective MWL scores, higher error rates, and longer reaction times in both conditions. However, the degree of immersion did not significantly influence subjective MWL ratings or performance metrics (ERs and RTs) when comparing the HMD and desktop conditions. Crucially, the EEG-derived MWL index revealed a significant difference between the two environments. While both conditions showed increased MWL compared to rest, the HMD condition resulted in a significantly lower EEG-based MWL index across most task levels compared to the desktop condition. This suggests that while participants perceived similar workload levels and performed similarly, their physiological cognitive load was lower in the immersive VR environment. The study concludes that immersive VR, specifically via HMDs, may reduce the physiological cognitive load associated with certain cognitive tasks compared to desktop interfaces, despite no significant difference in subjective perception or behavioral performance. This finding highlights the importance of using multimodal assessment, particularly physiological measures like EEG, to fully understand the effects of VR on mental workload. The reduced objective MWL in VR has implications for the design of VR-based applications in training, rehabilitation, and human-computer interaction, suggesting that immersive environments might offer a cognitively less demanding alternative to traditional screens for specific tasks.

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Topics

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• workload measurement
• neuro workload indices
• mental demand

Information type

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• Empirical Findings: physiological data, self report data