Sensors (Aug 2023)

A Comparative Study of the Typing Performance of Two Mid-Air Text Input Methods in Virtual Environments

  • Yueyang Wang,
  • Yahui Wang,
  • Xiaoqiong Li,
  • Chengyi Zhao,
  • Ning Ma,
  • Zixuan Guo

DOI
https://doi.org/10.3390/s23156988
Journal volume & issue
Vol. 23, no. 15
p. 6988

Abstract

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Inputting text is a prevalent requirement among various virtual reality (VR) applications, including VR-based remote collaboration. In order to eliminate the need for complex rules and handheld devices for typing within virtual environments, researchers have proposed two mid-air input methods—the trace and tap methods. However, the specific impact of these input methods on performance in VR remains unknown. In this study, typing tasks were used to compare the performance, subjective report, and cognitive load of two mid-air input methods in VR. While the trace input method was more efficient and novel, it also entailed greater frustration and cognitive workload. Fortunately, the levels of frustration and cognitive load associated with the trace input method could be reduced to the same level as those of the tap input method via familiarity with VR. These findings could aid the design of virtual input methods, particularly for VR applications with varying text input demands.

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