Electrotactile Assistive Tools to Support Blind and Low Vision People’s Data Comprehension

Being able to access and interpret data is a critical skill in today's world, but it remains challenging for blind and low vision (BLV) people.While the accessibility community has explored various solutions to make data more accessible, little is known about BLV people's daily data analysis (DDA) workflows and how haptic assistive tools, especially electrotactile devices, can support their data comprehension.To address these gaps, my dissertation investigates how BLV people engage in DDA and develops electrotactile assistive tools to support common scenarios such as chart and map understanding, and trip preview based on the study results.Through a series of user studies, I contribute empirical insights into five key strategies used by BLV people for DDA, and two electrotactile systems, providing evidence that these systems are effective when optimized for different scenarios.I plan to conduct further research on optimizing electrotactile feedback through a deeper understanding of its perceptual mechanisms, supported by AI-driven adaptation and personalization.