The Effect of Task Complexity on Time Perception in the Virtual Reality Environment: An EEG Study

Abstract

Background: Virtual reality (VR) technology is increasingly being utilized for multiple purposes. Unlike traditional 2D devices, VR headsets allow individuals to enjoy an immersive experience that includes multisensory interaction and a sense of presence. However, VR is not a perfect copy of the real world, and individuals may perceive differently on time in the virtual reality environment (VRE) than they do in their daily lives. Time perception is the process by which individuals subjectively judge the length of time and time duration estimation is proved a robust way to measure the time perception. As time perception is known as critical in the performance of time-related tasks, it is worth studying how time perception is affected in the VR applications. While the importance of time perception has been investigated, little is known about various factors’ influence on time estimation in the VRE. Given that both time perception and task complexity are associated with attentional resources, it merits investigating how time perception is influenced by task complexity in the VRE. Objective: The goal of this thesis study was to investigate the effect of task complexity on time perception in the VRE using behavioral, subjective, and physiological measurements. Three research questions were investigated in this study: (1) Does task complexity in the VRE affect time perception? (2) Does task complexity in the VRE affect brain signals? and (3) Are there relationships among time perception, brain signals, and subjective workload in the VRE? Methods: Twenty-nine participants performed a jigsaw puzzle task at different levels of task complexity (low and high) in the VRE. Each task was repeated three times. The independent variables were task complexity and the sequence of the block, and the dependent variables were time estimation error, electroencephalogram (EEG) as the physiological measurement, and the NASA-TLX score as the subjective workload measurement. Results: I found significant effects of task complexity on time estimation error and the NASA-TLX score. This result indicates when individuals conducted a more complex task, they may overestimate the elapsed time than the task actually takes and perceive a higher workload. Simultaneously, the maximum EEG amplitudes and the maximum high beta-band power at Cz, Fz, and Pz increase with the task complexity. The result also shows the sequence of the block only impacts the NASA-TLX score but has no significant effect on time estimation error or EEG signals. Finally, I found positive correlations between NASA-TLX score and time estimation error. Also, I observed significant correlation between NASA-TLX score and some brain signals—i.e., the maximum EEG amplitudes at Cz and Pz and the maximum high beta-band power at Cz, Fz and Pz. Implications: The results of the study demonstrate that higher task complexity negatively influences the accuracy of individuals’ time estimations in the VRE. To improve the performance of time-related tasks in the VRE, a modest-complexity design is recommended. The findings support the idea that using time estimation as an indicator of workload assessment in the VRE.