March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
Advanced Method Of Perceptual Training For Improving Near Visual Functions Using Mobile Devices
Author Affiliations & Notes
  • Uri Polat
    Faculty of Medicine, Goldshleger Eye Res Inst, Tel-Aviv Univ, Tel-Hashomer, Israel
  • Anna Sterkin
    Faculty of Medicine, Goldshleger Eye Res Inst, Tel-Aviv Univ, Tel-Hashomer, Israel
  • Oren Yehezkel
    Faculty of Medicine, Goldshleger Eye Res Inst, Tel-Aviv Univ, Tel-Hashomer, Israel
  • Maria Lev
    Faculty of Medicine, Goldshleger Eye Res Inst, Tel-Aviv Univ, Tel-Hashomer, Israel
  • Footnotes
    Commercial Relationships  Uri Polat, Ucansi Inc. (F, P); Anna Sterkin, None; Oren Yehezkel, None; Maria Lev, None
  • Footnotes
    Support  Ucansi Inc.
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 4817. doi:https://doi.org/
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    • Get Citation

      Uri Polat, Anna Sterkin, Oren Yehezkel, Maria Lev; Advanced Method Of Perceptual Training For Improving Near Visual Functions Using Mobile Devices. Invest. Ophthalmol. Vis. Sci. 2012;53(14):4817. doi: https://doi.org/.

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

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Abstract

Purpose: : Perceptual learning improves visual functions. In presbyopia, the visual input from the eye to the brain is limited by the optics of the eye. We showed (ARVO 2010, 2011) that perceptual learning in presbyopia leads to perceptual improvements without changes in the optical functions. Remarkable improvement was found in visual acuity (≈ 81%, 2.57 ± 0.03 ETDRS lines, mean ± se), contrast sensitivity, contrast discrimination, and reading speed. The training was performed on a PC at the user's home for 30-minute training sessions. Still, the relatively long-session duration and the large pixel size that limits the highest spatial frequency that can be presented challenged us to improve the technique. Therefore, we sought solutions to increase the quality of the image presentations and developed an advanced method for high resolution portable devices that overcome the technical limitations of the common PC devices.

Methods: : We adapted our structured method for improving visual functions in presbyopia to mobile devices (iPhone, iPad, iPod). To this end, subjects were trained on contrast detection of Gabor targets under backward masking conditions, posing temporal constraints on the visual processing. The training covered a range of spatial frequencies and orientations that were modified in accordance with the improvement of the subjects. The subjects were trained from a distance of 40 cm with both eyes open using shorter sessions of only 15 minutes per session for at least 3 times per week.

Results: : The resolution and the quality of the screens of smart phones are much better than those of the PC monitors. The range of the PC monitors’ pixel's size is 0.17-0.45 mm (0.27± 0.05, mean ± std; n=90), whereas it is 0.08 and 0.16 for iPhone 4 and iPhone 3, respectively. Thus, these devices enable one to achieve better contrast sensitivity by a factor of 2-3. The improvement in the visual functions is consistent with the previous results measuresd on the PC.

Conclusions: : Our method is effective in improving visual functions in people with presbyopia by enhancing the image representation in the brain. The results show that smartphones and mobile devices can be used as an effective solution for training near visual functions.

Keywords: plasticity • presbyopia • learning 
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