July 2018
Volume 59, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2018
Dynamic Pupil Tracking for Adaptive Optics Visual Simulator with Liquid Crystal Spatial Light Modulator
Author Affiliations & Notes
  • Fan Yi
    School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia
  • Brett A Davis
    School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia
  • Hamish McNeill
    School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia
  • Michael J Collins
    School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia
  • Footnotes
    Commercial Relationships   Fan Yi, None; Brett Davis, None; Hamish McNeill, None; Michael Collins, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 659. doi:https://doi.org/
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Fan Yi, Brett A Davis, Hamish McNeill, Michael J Collins; Dynamic Pupil Tracking for Adaptive Optics Visual Simulator with Liquid Crystal Spatial Light Modulator. Invest. Ophthalmol. Vis. Sci. 2018;59(9):659. doi: https://doi.org/.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : Pupil tracking is of importance for any adaptive optics (AO) application where a large amount of residual wavefront error can be induced by misalignment of the subject’s eye and the system’s optical axis. We developed a dynamic pupil tracker (DPT) for an AO visual simulator (AOVS) to minimize the error caused by misalignment and reduced the system’s dependence on a high-precision motor driven chin/head rest. The use of a bite bar can also be avoided after using the DPT, which provides the subjects with a more comfortable experience in long AO experiments.

Methods : The DPT is based on a high resolution Logitech digital webcam and driven by customized software written in Matlab. The camera acquires images over a 17.5 x 14 mm area of the eye illuminated by an NIR (950 nm) light source. Image processing algorithms are applied to obtain the real-time centre location and size of pupil. The coordinates of pupil centre are then fed to the liquid crystal spatial light modulator (SLM), which delivers the optical design to the eye at the real-time location of the pupil. The performance of the DPT was evaluated with a model eye and real eyes.

Results : The developed dynamic pupil tracking function feeds the eye location to the SLM at a speed of up to 90 Hz, has an x-y range of ±1.5 mm and a variable resolution of 15 ~60 µm/pixel across the pupil. The SLM used in the AOVS has 512 x 512 liquid crystal cells covering a 7.68 x 7.68 mm square working area and provides a spatial resolution of 15 µm. With pupil tracking on, the RMS of residual wavefront due to misalignment was reduced to about 14.2 ± 6.6% for AO wavefront correction and 16.5± 8% for wavefront combined with induced optical designs, depending on pupil offset.

Conclusions : Dynamic pupil tracking in an adaptive optics visual simulator is able to reduce the residual wavefront error produced by misalignment. This function can also be used by the AOVS to induce a predetermined amount of decentration to simulate the effect of lens offset with respect to the pupil.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

×
×

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.

×