June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Simulating the Effect of Acuity Reduction on Reading Performance
Author Affiliations & Notes
  • YINGZI XIONG
    University of Minnesota, Minneapolis, Minnesota, United States
  • Jeffrey Boucher
    University of Minnesota, Minneapolis, Minnesota, United States
    École Normale Supérieure, Paris, France
  • Aurelie Calabrese
    University of Minnesota, Minneapolis, Minnesota, United States
    Aix-Marseille University, Marseille, France
  • Quan Lei
    University of Minnesota, Minneapolis, Minnesota, United States
  • Gordon E Legge
    University of Minnesota, Minneapolis, Minnesota, United States
  • Footnotes
    Commercial Relationships   YINGZI XIONG, None; Jeffrey Boucher, None; Aurelie Calabrese, None; Quan Lei, None; Gordon Legge, None
  • Footnotes
    Support  NIH EY002934
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 3276. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to Subscribers Only
      Sign In or Create an Account ×
    • Get Citation

      YINGZI XIONG, Jeffrey Boucher, Aurelie Calabrese, Quan Lei, Gordon E Legge; Simulating the Effect of Acuity Reduction on Reading Performance. Invest. Ophthalmol. Vis. Sci. 2017;58(8):3276.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : Reduced visual acuity (VA) and contrast sensitivity (CS) are major contributors to reading problems in low vision. The current study investigates the impact of these variables on reading text by simulating different levels of low VA. A successful simulation would show approximately matched reading performance between normally sighted subjects with simulated VA and CS losses and corresponding low-vision subjects. Such a simulation could be useful in evaluating the accessibility of text for readers with different levels of low vision.

Methods : Low-pass spatial-frequency (SF) filters, created by shifting normal contrast-sensitivity functions (CSF) leftward along the SF axis (Lei et al., ARVO 2016), were used to simulate logMAR VA of 0, 0.3, 0.6, 0.9, 1.2 and 1.5. Calibration of the filters was confirmed by testing letter acuities after filtering. The filters were then applied to MNREAD charts to simulate reading with reduced VA. 38 normally sighted subjects were tested with the filtered charts. At each VA level, maximum reading speed (MRS), critical print size (CPS) and reading acuity (RA) were estimated to quantify reading performance. 14 subjects were tested with both Times and Courier fonts. Reading with the simulation was compared with MNREAD data from 43 actual low-vision subjects (Mean VA = 0.77 ± 0.06 logMAR).

Results : MNREAD results with the simulation showed linear relations for RA and CPS with reduced VA, while MRS remain constant at about 2.26 log wpm. Performance was better for Courier than Times in RA and CPS across all simulated VA levels, with a mean difference of 0.06 and 0.07 logMAR respectively. No font difference in MRS was observed. Comparison of MNREAD results between simulated and actual low vision with matched VA showed approximately matched RA (p = .42), while the simulation group had significantly faster MRS (p < .001) and smaller CPS (p = 0.032). Regression analysis of CPS against VA showed the same slopes (0.95) but different intercepts (0.38 and 0.58 logMAR for simulated and actual low vision), representing about 60% larger CPS for actual low-vision subjects.

Conclusions : Simulation of reading with reduced VA, based on a leftward-shifted CSF filter accounts for low-vision RA and places an upper bound on MRS and lower bound on CPS. Future incorporation of simulated CS reduction is expected to enhance the overall match between simulated and actual low-vision reading performance.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×