Although the interaction technology for virtual reality (VR) systems has evolved significantly over the past years, the text input efficiency in the virtual environment is still an ongoing problem. We deployed a word-gesture text entry technology based on gesture recognition in the virtual environment. This study aimed to investigate the performance of the word-gesture text entry technology with different input postures and VR experiences in the virtual environment. The study revealed that the VR experience (how long or how often using VR) had little effect on input performance. The hand-up posture has a better input performance when using word-gesture text entry technology in a virtual environment. In addition, the study found that the perceived exertion to complete the text input with word-gesture text entry technology was relatively high. Furthermore, the typing accuracy and perceived usability for using the hand-up posture were obviously higher than that for the hand-down posture. The hand-up posture also had less task workload than the hand-down posture. This paper supports that the word-gesture text entry technology with hand-up posture has greater application potential than hand-down posture.
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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