September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
An inexpensive smartphone-based eyewear for low-vision individuals
Author Affiliations & Notes
  • Olivia Walch
    Mathematics, University of Michigan, Ann Arbor, Michigan, United States
  • Matthew Jacobs
    Mathematics, University of Michigan, Ann Arbor, Michigan, United States
  • Kwoon Y Wong
    Ophthalmology & Visual Sciences, University of Michigan, Ann Arbor, Michigan, United States
  • Footnotes
    Commercial Relationships   Olivia Walch, None; Matthew Jacobs, None; Kwoon Wong, None
  • Footnotes
    Support  National Science Foundation DGE 1256260
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 5164. doi:
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      Olivia Walch, Matthew Jacobs, Kwoon Y Wong; An inexpensive smartphone-based eyewear for low-vision individuals. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5164.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Real-time electronic image processing is a promising approach to enhance the visual capability of low-vision individuals. A number of mobile, head-mounted low-vision aids have incorporated several image processing techniques such as magnification and contrast reversal, but unfortunately they all cost over $1000. We aim to develop and test an image-enhancing mobile application for Android and iOS which can be used in conjunction with inexpensive virtual reality (VR) headsets.

Methods : Using affordable phones (as cheap as $20) and VR headsets ($3 - $15), we have carried out real-time image processing with a mobile app for iOS and Android. The phone camera is used to stream real-time video on the phone screen, which is algorithmically processed to enhance certain features. The processed frame appears twice on the phone screen, which, when viewed through a VR headset, appears as a single 3-dimensional image. The app features multiple modes of operation, which can be toggled by pressing one volume button, and each mode has tunable parameters which can be used to further personalize the processing, controlled via the second volume button.

Results : We have successfully incorporated six methods of image processing into the app: edge enhancement, contrast enhancement, color reversal, magnification, “cartoonification”, and image remapping/retargeting for patients with central/peripheral vision loss. The app runs successfully and smoothly on a number of devices: iPhone 4S, iPhone 6, LG G Flex, Motorola Nexus 6, and Samsung Galaxy Avant. With an external battery pack attached, this app can run continuously for over a day. All users tested found at least one image-processing method beneficial.

Conclusions : Efficient real-time image processing is possible on most modern smartphones, including many discontinued phones that can be purchased used for well under $100. Furthermore, the kind and degree of processing can be user-adjusted to match the user's personal visual needs. In this way, visual enhancement can be carried out cheaply and with ubiquitous technology.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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