Abstract
This paper investigated the effect of task complexity on time estimation in the virtual reality environment (VRE) using behavioral, subjective, and physiological measurements. Virtual reality (VR) is not a perfect copy of the real world, and individuals perceive time duration differently in the VRE than they do in reality. Though many researchers have found a connection between task complexity and time estimation under non-VR conditions, the influence of task complexity on time estimation in the VRE is yet unknown. In this study, twenty-nine participants performed a VR jigsaw puzzle task at two levels of task complexity. We observed that as task complexity increased, participants showed larger time estimation errors, reduced relative beta-band power at Fz and Pz, and higher NASA-Task Load Index scores. Our findings indicate the importance of controlling task complexity in the VRE and demonstrate the potential of using electroencephalography (EEG) as real-time indicators of complexity level.
Highlights
Estimation in the Virtual RealityVirtual reality (VR) technology provides an immersive computer-generalized environment in which individuals are able to interact with multisensory input [1,2]
Because the head-mounted display (HMD) that is part of VR technology blocks real-world external stimuli, it is challenging for VR users to estimate the amount of time they have spent inside the virtual reality environment (VRE) [1]
We found that the participants made greater time estimation errors as the task complexity in the VRE increased
Summary
Estimation in the Virtual RealityVirtual reality (VR) technology provides an immersive computer-generalized environment in which individuals are able to interact with multisensory input [1,2]. Because the head-mounted display (HMD) that is part of VR technology blocks real-world external stimuli, it is challenging for VR users to estimate the amount of time they have spent inside the virtual reality environment (VRE) [1]. In the prospective time estimation paradigm, participants are informed that they are required to estimate duration prior to starting a task; in contrast, in the retrospective time estimation paradigm, participants are not informed that they are required to estimate duration prior to starting a task. Both paradigms ask participants about duration after the task [4,5]. Prospective time estimation is explained by the attention allocation model that fewer resources are available for processing time estimation when other cognitive tasks require more attentional resources [6,7,8]
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