Entropy of Controller Movements Reflects Mental Workload in Virtual Reality

Abstract

Virtual Reality can impose cognitive demands on users and influence their task performance. These cognitive demands, however, have been difficult to measure precisely without inducing breaks of presence. Based on findings in psychological science on how motion trajectories reflect underlying cognitive processes, we investigated entropy (i.e. the degree of movement irregularity) as an unobtrusive measure of mental workload. Entropy values were obtained from a time-series history of controller movement data. Mental workload is considered high over a given time interval, when the measured entropy is high as well. By manipulating the difficulty of a simple rhythm game we could show that the results are comparable to the results of the NASA-TLX questionnaire, which is currently used as the gold standard in VR for measuring mental workload. Thus, our results pave the way for further investigating the entropy of controller movements as a precise measurement of mental workload in VR.