Award Abstract # 1657315
CRII: CHS: Customized Navigation for Older Adults with Vision Loss

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: CORNELL UNIVERSITY
Initial Amendment Date: March 1, 2017
Latest Amendment Date: March 1, 2017
Award Number: 1657315
Award Instrument: Standard Grant
Program Manager: Ephraim Glinert
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: March 1, 2017
End Date: February 29, 2020 (Estimated)
Total Intended Award Amount: $175,000.00
Total Awarded Amount to Date: $175,000.00
Funds Obligated to Date: FY 2017 = $175,000.00
History of Investigator:
  • Shiri Azenkot (Principal Investigator)
    shiri.azenkot@cornell.edu
Recipient Sponsored Research Office: Cornell University
341 PINE TREE RD
ITHACA
NY  US  14850-2820
(607)255-5014
Sponsor Congressional District: 19
Primary Place of Performance: Cornell Tech
111 8th Ave #302
New York
NY  US  10011-5201
Primary Place of Performance
Congressional District:
10
Unique Entity Identifier (UEI): G56PUALJ3KT5
Parent UEI:
NSF Program(s): CRII CISE Research Initiation
Primary Program Source: 01001718DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7367, 8228
Program Element Code(s): 026Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

For a person with low vision, interacting with a smartphone to access information that is critical to their independence and safety, while possible, is slow and tedious. The ultimate goal of this research is to remedy that deficiency by creating technology that enables these users to access information quickly and easily, both at home and on the go. As a concrete and challenging first step, the work will focus on systems to enable seniors with low vision to plan and execute urban navigation tasks. If successful, members of this large and growing target community will be empowered to perform a key activity of daily living with more confidence and independence. Project outcomes will advance the state of the art in accessibility research more broadly, by laying the foundation for a new paradigm of accessible interaction via low-cost mainstream devices.

To these ends, the research will involve a number of phases: (1) documenting the navigation and mobility patterns and challenges facing members of the target user community; (2) the design and implementation of a desktop system that produces "optimal" routes based on feature accessibility along a given route; (3) the design and implementation of a smartphone navigation application that will provide accessible guidance including accessible maps; and (4) evaluation of the smartphone application in the field with target users. Achieving these goals will require an interdisciplinary effort that draws on expertise in a diverse set of fields, including accessibility, interaction techniques, information processing, and machine learning.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Zhao, Yuhang and Kupferstein, Elizabeth and Castro, Brenda Veronica and Feiner, Steven and Azenkot, Shiri "Designing AR Visualizations to Facilitate Stair Navigation for People with Low Vision" UIST 2019 , 2019 10.1145/3332165.3347906 Citation Details
Zhao, Yuhang and Kupferstein, Elizabeth and Tal, Doron and Azenkot, Shiri ""It Looks Beautiful but Scary": How Low Vision People Navigate Stairs and Other Surface Level Changes" Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 18) , 2018 10.1145/3234695.3236359 Citation Details
Zhao, Yuhang and Szpiro, Sarit and Shi, Lei and Azenkot, Shiri "Designing and Evaluating a Customizable Head-mounted Vision Enhancement System for People with Low Vision" ACM Transactions on Accessible Computing , v.12 , 2020 10.1145/3361866 Citation Details

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

While extensive prior research has investigated navigation for blind people and people with other disabilities, the navigation needs of older adults with low vision have not yet been systematically addressed. As the number of older adults with vision loss increases, this research will impact millions of people. The navigation assistance systems developed in this study will enable older adults to navigate new spaces, climb stairs, and identify text and images more easily, safely, and confidently. 

 

In this multi-step research project, we investigated the navigation and mobility needs of older adults with vision loss, created technologies that detect obstacles and highlight safe routes, designed usable interfaces for these systems, and evaluated these prototypes with the target population. In a first study, we interviewed and observed participants with low vision as they navigated indoor and outdoor spaces. This study showed that stairs and surface level changes (e.g., curbs and sidewalk cracks) are a source of difficulty for many participants. In most cases, these were more difficult for participants to navigate than other features in the environment, such as obstacles or street intersections. Unlike blind people, our participants with low vision used their vision extensively when navigating, sometimes using a cane as a supplement. While they preferred to use their vision, they still felt unsafe and insecure.

 

In a series of follow-up studies, we designed technologies that enable users to more easily navigate stairs and wayfind in unfamiliar indoor spaces, and created interfaces that make these systems easy to use. We leveraged commercially available augmented and virtual reality systems to enhance a user’s environment directly. To support navigation, we designed virtual contrast stripes to augment the edges of stairs to facilitate stair navigation, and designed a virtual path and spatial audio guidance instructions to support wayfinding. In addition, we designed a vision enhancement system that incorporated customizable magnification, contrast enhancement, and other basic video refinement algorithms to support general near and distance viewing tasks. We evaluated our new interfaces for each task with target users, showing that participants achieved better performance with our designs than with baseline. Overall, our studies highlighted the importance of allowing users to combine visual and audio feedback and customize interfaces to fit their preferences and particular vision needs.


Last Modified: 04/01/2020
Modified by: Shiri Azenkot

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