Low-Cost Real-Time Mental Load Adaptation for Augmented Reality Instructions – A Feasibility Study

Since the introduction of augmented reality (AR) technology, in-situ
instructions for manual tasks have been a central use case for a large
body of previous work. However, most implementations provide
identical sets of instructions to each user disregarding the user’s
current mental load. This is a major issue since previous work has
shown the importance and potential of an adapted instruction fidelity
for manual tasks such as playing an instrument. To implement a
low-cost mental load adaptation for AR instructions, we evaluated a
mobile off-the-shelf electroencephalographic (EEG) device for its
suitability and feasibility to measure mental load while wearing a
video see-through AR head-mounted display (HMD). In a first user
experiment (n=12), data of EEG power band values and proprietary
performance metrics of the manufacturer were collected and analysed
regarding their validity to estimate the user’s mental load. Our
results indicate that our setup successfully induced different levels of
mental effort. The proprietary performance metrics, however, only
partially reflected the participants’ current mental effort and require
further analysis.

Published in Adjunct Proceedings of ISMAR 2019


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