Frontiers in Human Neuroscience (Nov 2019)

Estimating Cognitive Workload in an Interactive Virtual Reality Environment Using EEG

  • Christoph Tremmel,
  • Christian Herff,
  • Tetsuya Sato,
  • Krzysztof Rechowicz,
  • Yusuke Yamani,
  • Dean J. Krusienski

DOI
https://doi.org/10.3389/fnhum.2019.00401
Journal volume & issue
Vol. 13

Abstract

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With the recent surge of affordable, high-performance virtual reality (VR) headsets, there is unlimited potential for applications ranging from education, to training, to entertainment, to fitness and beyond. As these interfaces continue to evolve, passive user-state monitoring can play a key role in expanding the immersive VR experience, and tracking activity for user well-being. By recording physiological signals such as the electroencephalogram (EEG) during use of a VR device, the user's interactions in the virtual environment could be adapted in real-time based on the user's cognitive state. Current VR headsets provide a logical, convenient, and unobtrusive framework for mounting EEG sensors. The present study evaluates the feasibility of passively monitoring cognitive workload via EEG while performing a classical n-back task in an interactive VR environment. Data were collected from 15 participants and the spatio-spectral EEG features were analyzed with respect to task performance. The results indicate that scalp measurements of electrical activity can effectively discriminate three workload levels, even after suppression of a co-varying high-frequency activity.

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