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A Comparative Study of the Typing Performance of Two Mid-Air Text Input Methods in Virtual Environments.
Wang, Yueyang; Wang, Yahui; Li, Xiaoqiong; Zhao, Chengyi; Ma, Ning; Guo, Zixuan.
Afiliação
  • Wang Y; The School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China.
  • Wang Y; The School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China.
  • Li X; The School of Life Science, Beijing Institute of Technology, Beijing 100081, China.
  • Zhao C; Faculty of Psychology, Beijing Normal University, Beijing 100875, China.
  • Ma N; Department of Design, Kyiv National University of Technologies and Design, 01011 Kyiv, Ukraine.
  • Guo Z; Faculty of Psychology, Beijing Normal University, Beijing 100875, China.
Sensors (Basel) ; 23(15)2023 Aug 06.
Article em En | MEDLINE | ID: mdl-37571771
ABSTRACT
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carga de Trabalho / Realidade Virtual Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carga de Trabalho / Realidade Virtual Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China