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Exploring Data Input Problems in Mixed Reality Environments: Proposal and Evaluation of Natural Interaction Techniques

Author

Listed:
  • Jingzhe Zhang

    (School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China)

  • Tiange Chen

    (School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China)

  • Wenjie Gong

    (School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China)

  • Jiayue Liu

    (School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China)

  • Jiangjie Chen

    (School of Design, Jiangnan University, Wuxi 214122, China)

Abstract

Data input within mixed reality environments poses significant interaction challenges, notably in immersive visual analytics applications. This study assesses five numerical input techniques: three benchmark methods (Touch-Slider, Keyboard, Pinch-Slider) and two innovative multimodal techniques (Bimanual Scaling, Gesture and Voice). An experimental design was employed to compare these techniques’ input efficiency, accuracy, and user experience across varying precision and distance conditions. The findings reveal that multimodal techniques surpass slider methods in input efficiency yet are comparable to keyboards; the voice method excels in reducing cognitive load but falls short in accuracy; and the scaling method marginally leads in user satisfaction but imposes a higher physical load. Furthermore, this study outlines these techniques’ pros and cons and offers design guidelines and future research directions.

Suggested Citation

  • Jingzhe Zhang & Tiange Chen & Wenjie Gong & Jiayue Liu & Jiangjie Chen, 2024. "Exploring Data Input Problems in Mixed Reality Environments: Proposal and Evaluation of Natural Interaction Techniques," Future Internet, MDPI, vol. 16(5), pages 1-15, April.
    • Handle: RePEc:gam:jftint:v:16:y:2024:i:5:p:150-:d:1384265
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