Evidence map›Paper›PMID 30650159›Full record

ArticlePloS one2019

An augmented reality sign-reading assistant for users with reduced vision.

Jonathan Huang, Max Kinateder, Matt J Dunn, Wojciech Jarosz, Xing-Dong Yang, Emily A Cooper

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
5.1field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. VisiMark: Characterizing and Augmenting Landmarks for People with Low Vision in Augmented Reality to Support Indoor Navigation.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2025
    Article
  4. Article
  5. CookAR: Affordance Augmentations in Wearable AR to Support Kitchen Tool Interactions for People with Low Vision.Proceedings of the ACM Symposium on User Interface Software and Technology. ACM Symposium on User Interface Software and Technology · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Navigational aid use by individuals with visual impairments.Journal on technology and persons with disabilities : ... Annual International Technology and Persons with Disabilities Conference · 2020
    Article
  12. Virtual Reality and Augmented Reality in Ophthalmology: A Contemporary Prospective.Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Jonathan HuangDepartment of Computer Science, Dartmouth College, Hanover, New Hampshire, United States of America.
Max KinatederDepartment of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, United States of America.
Matt J DunnSchool of Optometry and Vision Sciences, Cardiff University, Cardiff, United Kingdom.ORCID 0000-0002-0295-2182
Wojciech JaroszDepartment of Computer Science, Dartmouth College, Hanover, New Hampshire, United States of America.
Xing-Dong YangDepartment of Computer Science, Dartmouth College, Hanover, New Hampshire, United States of America.
Emily A CooperDepartment of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, United States of America.ORCID 0000-0003-4889-7446
Dartmouth College · USCardiff University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

People typically rely heavily on visual information when finding their way to unfamiliar locations. For individuals with reduced vision, there are a variety of navigational tools available to assist with this task if needed. However, for wayfinding in unfamiliar indoor environments the applicability of existing tools is limited. One potential approach to assist with this task is to enhance visual information about the location and content of existing signage in the environment. With this aim, we developed a prototype software application, which runs on a consumer head-mounted augmented reality (AR) device, to assist visually impaired users with sign-reading. The sign-reading assistant identifies real-world text (e.g., signs and room numbers) on command, highlights the text location, converts it to high contrast AR lettering, and optionally reads the content aloud via text-to-speech. We assessed the usability of this application in a behavioral experiment. Participants with simulated visual impairment were asked to locate a particular office within a hallway, either with or without AR assistance (referred to as the AR group and control group, respectively). Subjective assessments indicated that participants in the AR group found the application helpful for this task, and an analysis of walking paths indicated that these participants took more direct routes compared to the control group. However, participants in the AR group also walked more slowly and took more time to complete the task than the control group. The results point to several specific future goals for usability and system performance in AR-based assistive tools.

Indexed as

Persons with Visual DisabilitiesVirtual RealityFemaleHumansMaleUser-Computer InterfaceYoung Adult

Identifiers

PMID30650159
PMCPMC6334915
OpenAlexW2909795082

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.