OpticalAging: Real-time Presbyopia Simulation for Inclusive Design via Tunable Lenses

TL;DR

OpticalAging addresses the gap in understanding presbyopia for non-presbyopes by offering a real-time, optical see-through simulation using tunable lenses to induce distance-dependent blur during real-world tasks. The method combines quantitative near-point validation with qualitative insights from designers, showing that embodied exposure to presbyopic constraints can increase awareness and influence inclusive design practices. Key contributions include a novel tunable-lens OST system, a calibration-driven algorithm for age-mode blur, and evidence that the approach can function as a productive design probe alongside direct user engagement. The work has practical impact for accelerating age-inclusive design workflows and lays groundwork for extending the approach to additional visual conditions.

Abstract

Presbyopia, a common age-related vision condition affecting most people as they age, often remains inadequately understood by those unaffected. To help bridge the gap between abstract accessibility knowledge and a more grounded appreciation of perceptual challenges, this study presents OpticalAging, an optical see-through simulation approach. Unlike VR-based methods, OpticalAging uses dynamically controlled tunable lenses to simulate the first-person visual perspective of presbyopia's distance-dependent blur during real-world interaction, aiming to enhance awareness. While acknowledging critiques regarding simulation's limitations in fully capturing lived experience, we position this tool as a complement to user-centered methods. Our user study (N = 19, 18-35 years old) provides validation: quantitative measurements show statistically significant changes in near points across three age modes (40s, 50s, 60s), while qualitative results suggest increases in self-reported understanding and awareness of perceptual challenges among participants. The integration of our tool into a design task showcases its potential applicability within age-inclusive design workflows when used critically alongside direct user engagement.

Figures (10)

• Figure 1: Configuration and calibration of the tunable lenses eyewear for presbyopia simulation. (A) Front view of the eyewear, showing the placement of the focal tunable lenses and the Time of Flight (TOF) distance sensor. (B) Adjustable features of the tunable lens eyewear to accommodate individual differences, including interpupillary distance (PD) adjustment, adjustable left temple, and a focal length adjusting dial. (C) A participant wearing the calibrated eyewear, with proper PD and corrective power settings applied.
• Figure 2: Approach and interface for presbyopia simulation using tunable lenses. (A) Illustration of the primary algorithm: The tunable lenses simulate presbyopic blur by functioning as concave lenses to reduce the overall diopter of the wearer when the viewing distance is less than a preset near point (e.g., 25 cm for 40s mode). Beyond this point, the lenses work as corrective mode to adjust dynamically based on viewing distance. (B) Operational graphical interface for individual calibration, allowing separate focal power correction for each eye to accommodate wearers with refractive errors.
• Figure 3: Workflow of the presbyopia simulation algorithm. The flowchart illustrates the decision-making process for simulating presbyopic blur based on the chosen age mode, wearer's age, and viewing distance relative to the preset near point range.
• Figure 4: A participant wearing the tunable lens eyewear is shown with a mobile board displaying printed text moving towards them. This setup mimics the Push-Up test commonly used in ophthalmology to measure near point accommodation. The participant's jaw rests on a table to minimize head displacement, ensuring consistent and reliable measurements.
• Figure 5: This plot includes data for the baseline (no simulation, natural near point) and simulated conditions representing optically shifted near point of 40s, 50s, and 60s for 19 participants. Each box represents the interquartile range (IQR) with the median indicated by the central line. Whiskers extend to the minimum and maximum values within 1.5 times the IQR. Outliers, marked with 'x', are data points beyond the whiskers. The plot demonstrates a clear progression in near point distances as the simulated age increases. Statistical analysis confirmed significant differences between all simulation modes ($p < .001$ for all pairwise comparisons).