Estimating the Effects of Encumbrance and Walking on Mixed Reality Interaction

要旨

This paper investigates the effects of two situational impairments---encumbrance (i.e., carrying a heavy object) and walking---on interaction performance in canonical mixed reality tasks. We built Bayesian regression models of movement time, pointing offset, error rate, and throughput for target acquisition task, and throughput, UER, and CER for text entry task to estimate these effects. Our results indicate that 1.0 kg encumbrance increases selection movement time by 28%, decreases text entry throughput by 17%, and increase UER by 50%, but does not affect pointing offset. Walking led to a 63% increase in ray-cast movement time and a 51% reduction in text entry throughput. It also increased selection pointing offset by 16%, ray-cast pointing offset by 17%, and error rate by 8.4%. The interaction effect on 1.0 kg encumbrance and walking resulted in a 112% increase in ray-cast movement time. Our findings enhance the understanding of the effects of encumbrance and walking on mixed reality interaction, and contribute towards accumulating knowledge of situational impairments research in mixed reality.

受賞
Honorable Mention
著者
Tinghui Li
University of Sydney, Sydney, Australia
Eduardo Velloso
University of Sydney, Sydney, New South Wales, Australia
Anusha Withana
The University of Sydney, Sydney, NSW, Australia
Zhanna Sarsenbayeva
University of Sydney, Sydney, Australia
DOI

10.1145/3706598.3713492

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713492

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Virtual and Mixed Reality Interaction

Annex Hall F204
7 件の発表
2025-04-30 23:10:00
2025-05-01 00:40:00
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