April 2009
Volume 50, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2009
Automated Testing of Super Vision and Night Vision Performance
Author Affiliations & Notes
  • B. W. Davies
    Ophthalmology, Wilford Hall Medical Center, San Antonio, Texas
  • J. Rabin
    Ophthalmology, US Air Force School of Aerospace Medicine, San Antonio, Texas
  • J. Gooch
    Ophthalmology, US Air Force School of Aerospace Medicine, San Antonio, Texas
  • C. Reilly
    Ophthalmology, Wilford Hall Medical Center, San Antonio, Texas
  • R. Rubin
    Ophthalmology, US Air Force School of Aerospace Medicine, San Antonio, Texas
  • K. Stevens
    Ophthalmology, US Air Force School of Aerospace Medicine, San Antonio, Texas
  • S. Linnemeyer
    Ophthalmology, US Air Force School of Aerospace Medicine, San Antonio, Texas
  • M. Foxworth
    Ophthalmology, US Air Force School of Aerospace Medicine, San Antonio, Texas
  • Footnotes
    Commercial Relationships  B.W. Davies, None; J. Rabin, None; J. Gooch, None; C. Reilly, None; R. Rubin, None; K. Stevens, None; S. Linnemeyer, None; M. Foxworth, None.
  • Footnotes
    Support  None.
Investigative Ophthalmology & Visual Science April 2009, Vol.50, 1999. doi:
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    • Get Citation

      B. W. Davies, J. Rabin, J. Gooch, C. Reilly, R. Rubin, K. Stevens, S. Linnemeyer, M. Foxworth; Automated Testing of Super Vision and Night Vision Performance. Invest. Ophthalmol. Vis. Sci. 2009;50(13):1999.

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

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Abstract

Purpose: : Recent advances in optical wavefront technology have made it possible to achieve exceptional ("super") vision. But few clinical tests quantify extraordinary levels of vision and no clinical test or standard exists to ensure adequate night vision or night vision goggle (NVG) performance. We describe design and validation results for a new computer-based method to quantify super vision and night vision in a clinical setting.

Methods: : The automated test, based on the Super Vision Letter Chart Test (Prevision-Vision®) includes high contrast visual acuity (VA) and small letter contrast sensitivity (CS; 20/25 letters). In both tests a single letter appears briefly in the center of a computer display and the subject reports the letter aloud. The letters decrease progressively in size (VA; 20/32 to 20/6.3; 0.1 log MAR steps; 5 letters per step) or in contrast (CS; 20/25 letter sequence decreases in contrast from 56% to 1% in 0.25 log steps; 5 letters/step). Both VA and CS are viewed photopically (100 cd/m2 white display background), with VA also tested on a dark green display (4 & 1 cd/m2) to simulate brightness and color of NVGs. Performance on the automated test was compared to the standard letter chart version in 20 subjects tested in a repeated measures design.

Results: : Two-way ANOVA showed a significant effect of luminance on VA (F= 87, p<0.0001) and a significant interaction (F=3.4, p<0.05) with the automated test showing lower VA than the standard test at reduced luminance (mean decrease 0.08 log MAR). There was no difference between automated and letter chart tests at photopic levels for VA (p>0.45) or CS (p>0.15)

Conclusions: : Automated testing of super vision compares favorably to standard letter chart testing at photopic levels, and offers the advantage of computer-controlled letter randomization and automated scoring. However, performance was reduced on the automated low-luminance NVG test, due to the limited exposure time of the letters (more time needed at low luminance). Modifications are underway to increase letter exposure interval and to record patient reaction time as an additional index of performance.

Keywords: aberrations • contrast sensitivity • visual acuity 
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