Exploring usability of mobile vision assist applications for people with vision impairment

Mobile vision assist applications offer critical support for blind and low vision individuals in performing everyday tasks, yet few studies have examined their real-world usability. This study explored two widely used applications - SeeingAI and Sullivan+-through observations and focus group interviews with 17 blind and low vision participants in South Korea performing personal hygiene, shopping, and restroom navigation tasks. Thematic analysis revealed four key themes: (1) Variable Information Preferences Across Contexts, where participants required different information granularity based on situational needs and privacy concerns; (2) Interaction Efficiency and Operational Guidance Challenges, with difficulties from manual capture requirements, lack of camera positioning feedback, and processing delays; (3) Application and System Integration and Compatibility Barriers, highlighting disruptions from inter-application switching and poor accessibility tool integration; and (4) Technology Access and Knowledge Disparities, revealing how educational opportunities, financial constraints, and information dissemination pathways create unequal access within the blind and low vision community. Design recommendations include context-aware information delivery, conversational interfaces, hybrid recognition modes, seamless system integration, and device-agnostic functionality. These findings inform development of more inclusive mobile vision assist applications that support independent living while addressing systemic barriers to equitable technology access.