Examining Augmented Virtuality Impairment Simulation for Mobile App Accessibility Design

TL;DR

This paper tackles how to improve mobile app accessibility for cataract-impaired elderly users by evaluating Empath-D, an augmented virtuality impairment simulator. Through two studies, it shows that designer-developers using Empath-D identify more cataract-related usability challenges and implement more effective accessibility improvements than when using Google Accessibility Scanner with WCAG 2.0 guidelines. Empath-D yields higher accuracy and broader coverage, including detection of letter-spacing issues that GAS often misses, though automated tools still exhibit limitations. The work argues for combining immersive impairment simulations with targeted guidelines and proposes building a library of impairments to broaden design testing. Overall, Empath-D offers a practical, realism-enhancing approach to designing mobile apps that are more accessible to elderly users with visual impairments, with implications for future tool development and accessibility research.

Abstract

With mobile apps rapidly permeating all aspects of daily living with use by all segments of the population, it is crucial to support the evaluation of app usability for specific impaired users to improve app accessibility. In this work, we examine the effects of using our \textit{augmented virtuality} impairment simulation system--\textit{Empath-D}--to support experienced designer-developers to redesign a mockup of commonly used mobile application for cataract-impaired users, comparing this with existing tools that aid designing for accessibility. We show that the use of augmented virtuality for assessing usability supports enhanced usability challenge identification, finding more defects and doing so more accurately than with existing methods. Through our user interviews, we also show that augmented virtuality impairment simulation supports realistic interaction and evaluation to provide a concrete understanding over the usability challenges that impaired users face, and complements the existing guidelines-based approaches meant for general accessibility.

Figures (7)

• Figure 1: Composing the augmented virtuality view in Empath-D
• Figure 2: First page of the mockup baseline design used for S2 with example labels of UI elements used in the analysis. Image source: Instagram, © franniethepug
• Figure 3: All participants had similar mild-moderate (between 2: "some difficulty" to 3: "great difficulty") levels of cataract impairments.
• Figure 4: Coverage matrix of the usability challenges positively/negatively addressed by designer-developers. RGB]159,205,98a indicates challenges identified only by Empath-D (C1). RGB]236,50,36b indicates challenges identified only by Google Accessibility Scanner (C2). RGB]103,155,207c indicates challenges identified by both Empath-D and Google Accessibility Scanner. Blank cells indicate that no users identified challenges in either condition for that UI element.
• Figure 5: Balancing interaction design. Left: Unmodified base app. Centre: Design from P8 (C2: Google Accessibility Scanner) with very large like and bookmark buttons sacrificing content and interaction. Right: Design from P10 (C1: Empath-D) showing balance in design despite changes made to increase elements. Image source: Instagram, © franniethepug