@ UMD Intelligent Assistive Machines Lab
Datasets and data sharing play an important role in technological innovation but available data in wellness, accessibility, and aging are limited due to smaller populations, disparate characteristics, as well as lack of expertise for data annotation. The goal of this project is to mitigate the issues regarding inclusivity of data-driven methods and technologies.
@ CMU Cognitive Assistance Lab
We conducted multiple user studies to identify information requirements and implications for assistive technologies that support blind navigation and exploration inside complex buildings, including large hospitals and shopping malls. The studies include observation of how a prototype navigation system might help.
@ UTokyo Y.Sato Lab
This work investigates remote guide performances in assisting people with visual impairments in indoor navigation. Based on our comparative analysis of trained and untrained guides as remote guides, we have extracted social and technical recommendations to maximize training opportunities for untrained remote guides and improve the current design of remote mobility assistance.