User-Centered Design of a Depth Data Based Obstacle Detection and Avoidance System for the Visually Impaired

Rabia Jafri and Marwa Mahmoud Khan, Human-centric Computing and Information Sciences, Springer Berlin Heidelberg, 2018, Volume 8, Issue 14.

Abstract: The development of a novel depth-data based real-time obstacle detection and avoidance application for visually impaired (VI) individuals to assist them in navigating independently in indoors environments is presented in this paper. The application utilizes a mainstream, computationally efficient mobile device as the development platform in order to create a solution which not only is aesthetically appealing, cost-effective, lightweight and portable but also provides real-time performance and freedom from network connectivity constraints. To alleviate usability problems, a user-centered design approach has been adopted wherein semi-structured interviews with VI individuals in the local context were conducted to understand their micro-navigation practices, challenges and needs. The invaluable insights gained from these interviews have not only informed the design of our system but would also benefit other researchers developing similar applications. The resulting system design along with a detailed description of its obstacle detection and unique multimodal feedback generation modules has been provided. We plan to iteratively develop and test the initial prototype of the system with the end users to resolve any usability issues and better adapt it to their needs.

View the complete article here: https://doi.org/10.1186/s13673-018-0134-9