Resolution deficits drive simulator sickness and compromise reading performance in virtual environments

TL;DR

This work investigates how end-to-end effective resolution, expressed in $logMAR$, drives simulator sickness and reading performance in VR and VST. It introduces XR-Read, a cross-language reading acuity test that precisely controls effective resolution and runs on VR and smartphone displays, enabling within-subject assessments of reading metrics and SSQ across English and Chinese. In a study with 16 participants across four resolution levels, reading performance degrades exponentially as clarity worsens, while simulator sickness rises, with a clear tipping point near $0$ logMAR where naked-eye performance is approached and sickness remains modest. The authors provide generalized reference curves linking logMAR to reading metrics and SSQ, along with design guidelines—highlighting the need to target $\leq 0$ logMAR for sustained, text-heavy XR use and to account for VST-specific penalties in budgets—thereby offering practical targets for typography, rendering, and QA in future XR systems.

Abstract

Extended reality (XR) is evolving into a general-purpose computing platform, yet its adoption for productivity is hindered by visual fatigue and simulator sickness. While these symptoms are often attributed to latency or motion conflicts, the precise impact of textual clarity on physiological comfort remains undefined. Here we show that sub-optimal effective resolution, the clarity that reaches the eye after the full display-optics-rendering pipeline, is a primary driver of simulator sickness during reading tasks in both virtual reality and video see-through environments. By systematically manipulating end-to-end effective resolution on a unified logMAR scale, we measured reading psychophysics and sickness symptoms in a controlled within-subjects study. We find that reading performance and user comfort degrade exponentially as resolution drops below 0 logMAR (normal visual acuity). Notably, our results reveal 0 logMAR as a key physiological tipping point: resolutions better than this threshold yield naked-eye-level performance with minimal sickness, whereas poorer resolutions trigger rapid, non-linear increases in nausea and oculomotor strain. These findings suggest that the cognitive and perceptual effort required to resolve blurry text directly compromises user comfort, establishing human-eye resolution as a critical baseline for the design of future ergonomic XR systems.

Figures (7)

• Figure 1: Screenshots of English ((a) and (c)) and Chinese ((b) and (d)) sentences from XR-Read. The first row shows the 2D XR-Read captured on a smartphone. The second row shows 3D XR-Read views captured in the Unity editor, where the blue arrow indicates the direction of the eye camera.
• Figure 2: Pictures of the 2D XR-Read on a smartphone and the chin rest. (a) and (b) show the experiment setup without and with a participant wearing the Varjo XR-4 Focal Edition.
• Figure 3: Mapping between render resolution scale and effective resolution in VR. The logarithmic regression $y=-0.28\ln(x)-0.02$ describes the relationship between render resolution scale $x$ and visual acuity (logMAR) $y$, measured with the OVVA test. Red markers (A--D) indicate the four target acuity levels (A = 0.00, B = 0.22, C = 0.40, D = 0.60 logMAR) and their corresponding scales ($x \approx$ 0.92, 0.42, 0.22, 0.11), with dashed lines projected to the axes.
• Figure 4: Violin plots with post-hoc results of XR-Read. '*' to '***' represent Bonferroni-adjusted significant differences at '.05', '.01', '.001' level.
• Figure 5: Violin plots with post-hoc results of Simulator Sickness Questionnaire. '*' to '***' represent Bonferroni-adjusted significant differences at '.05', '.01', '.001' level.