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Evaluating the efficacy of UNav: A computer vision-based navigation aid for persons with blindness or low vision.
Yang, Anbang; Tamkittikhun, Nattachart; Hamilton-Fletcher, Giles; Ramdhanie, Vinay; Vu, Thu; Beheshti, Mahya; Hudson, Todd; Riewpaiboon, Wachara; Mongkolwat, Pattanasak; Feng, Chen; Rizzo, John-Ross.
Affiliation
  • Yang A; Department of Mechanical and Aerospace Engineering, NYU Tandon School of Engineering, Brooklyn, New York, USA.
  • Tamkittikhun N; Faculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand.
  • Hamilton-Fletcher G; Department of Rehabilitation Medicine, NYU Grossman School of Medicine, New York, New York, USA.
  • Ramdhanie V; Department of Ophthalmology, NYU Grossman School of Medicine, New York, New York, USA.
  • Vu T; Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, New York, USA.
  • Beheshti M; Department of Computer Science and Engineering, NYU Tandon School of Engineering, Brooklyn, New York, USA.
  • Hudson T; Department of Rehabilitation Medicine, NYU Grossman School of Medicine, New York, New York, USA.
  • Riewpaiboon W; Department of Rehabilitation Medicine, NYU Grossman School of Medicine, New York, New York, USA.
  • Mongkolwat P; Ratchasuda Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Nakhon Pathom, Thailand.
  • Feng C; Faculty of Information and Communication Technology, Mahidol University, Nakhon Pathom, Thailand.
  • Rizzo JR; Department of Mechanical and Aerospace Engineering, NYU Tandon School of Engineering, Brooklyn, New York, USA.
Assist Technol ; : 1-15, 2024 Aug 13.
Article in En | MEDLINE | ID: mdl-39137956
ABSTRACT
UNav is a computer-vision-based localization and navigation aid that provides step-by-step route instructions to reach selected destinations without any infrastructure in both indoor and outdoor environments. Despite the initial literature highlighting UNav's potential, clinical efficacy has not yet been rigorously evaluated. Herein, we assess UNav against standard in-person travel directions (SIPTD) for persons with blindness or low vision (PBLV) in an ecologically valid environment using a non-inferiority design. Twenty BLV subjects (age = 38 ± 8.4; nine females) were recruited and asked to navigate to a variety of destinations, over short-range distances (<200 m), in unfamiliar spaces, using either UNav or SIPTD. Navigation performance was assessed with nine dependent variables to assess travel confidence, as well as spatial and temporal performances, including path efficiency, total time, and wrong turns. The results suggest that UNav is not only non-inferior to the standard-of-care in wayfinding (SIPTD) but also superior on 8 out of 9 metrics, as compared to SIPTD. This study highlights the range of benefits computer vision-based aids provide to PBLV in short-range navigation and provides key insights into how users benefit from this systematic form of computer-aided guidance, demonstrating transformative promise for educational attainment, gainful employment, and recreational participation.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Assist Technol Journal subject: REABILITACAO Year: 2024 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Assist Technol Journal subject: REABILITACAO Year: 2024 Document type: Article Affiliation country: