AlphaPIG: The Nicest Way to Prolong Interactive Gestures in Extended Reality

要旨

Mid-air gestures serve as a common interaction modality across Extended Reality (XR) applications, enhancing engagement and ownership through intuitive body movements. However, prolonged arm movements induce shoulder fatigue—known as "Gorilla Arm Syndrome"—degrading user experience and reducing interaction duration. Although existing ergonomic techniques derived from Fitts' law (such as reducing target distance, increasing target width, and modifying control-display gain) provide some fatigue mitigation, their implementation in XR applications remains challenging due to the complex balance between user engagement and physical exertion. We present \textit{AlphaPIG}, a meta-technique designed to \textbf{P}rolong \textbf{I}nteractive \textbf{G}estures by leveraging real-time fatigue predictions. AlphaPIG assists designers in extending and improving XR interactions by enabling automated fatigue-based interventions. Through adjustment of intervention timing and intensity decay rate, designers can explore and control the trade-off between fatigue reduction and potential effects such as decreased body ownership. We validated AlphaPIG's effectiveness through a study (N=22) implementing the widely-used Go-Go technique. Results demonstrated that AlphaPIG significantly reduces shoulder fatigue compared to non-adaptive Go-Go, while maintaining comparable perceived body ownership and agency. Based on these findings, we discuss positive and negative perceptions of the intervention. By integrating real-time fatigue prediction with adaptive intervention mechanisms, AlphaPIG constitutes a critical first step towards creating fatigue-aware applications in XR.

著者
Yi Li
Monash University, Melbourne, Australia
Florian Fischer
University of Cambridge, Cambridge, United Kingdom
Tim Dwyer
Monash University, Melbourne, VIC, Australia
Barrett Ens
The University of British Columbia (Okanagan Campus), Kelowna, British Columbia, Canada
Robert Crowther
University of New England, Armidale, New South Wales, Australia
Per Ola Kristensson
University of Cambridge, Cambridge, United Kingdom
Benjamin Tag
Monash University, Melbourne, Victoria, Australia
DOI

10.1145/3706598.3714249

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714249

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: Interfaces and Interactions for XR

G414+G415
6 件の発表
2025-05-01 01:20:00
2025-05-01 02:50:00
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