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

Jingzhe Zhang, Tiange Chen, Wenjie Gong, Jiayue Liu and Jiangjie Chen ()
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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

Future Internet, 2024, vol. 16, issue 5, 1-15

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.

Keywords: human–computer interaction; mixed reality; natural interaction techniques; immersive analytics; multimodal interaction techniques (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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