Designing Fatigue-Aware VR Interfaces via Biomechanical Models
Harshitha Voleti, Charalambos Poullis

TL;DR
This paper introduces a biomechanical model-based reinforcement learning framework to optimize VR interface layouts for reduced arm fatigue, validated by human studies, marking a novel approach in ergonomic VR UI design.
Contribution
It presents the first use of simulated biomechanical muscle fatigue as an optimization signal for VR UI layout, improving ergonomic design with less human testing.
Findings
RL-optimized layout reduces perceived fatigue in humans
Biomechanical fatigue trends align with human data
Framework extends to longer, complex tasks
Abstract
Prolonged mid-air interaction in virtual reality (VR) causes arm fatigue and discomfort, negatively affecting user experience. Incorporating ergonomic considerations into VR user interface (UI) design typically requires extensive human-in-the-loop evaluation. Although biomechanical models have been used to simulate human behavior in HCI tasks, their application as surrogate users for ergonomic VR UI design remains underexplored. We propose a hierarchical reinforcement learning framework that leverages biomechanical user models to evaluate and optimize VR interfaces for mid-air interaction. A motion agent is trained to perform button-press tasks in VR under sequential conditions, using realistic movement strategies and estimating muscle-level effort via a validated three-compartment control with recovery (3CC-r) fatigue model. The simulated fatigue output serves as feedback for a UI…
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