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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

A Robust and Reliable Test to Measure Stereopsis in the Clinic

Hess, R.F., Ding, R., Clavagnier, S., Liu, C., Guo, C., Viner, Catherine, Barrett, Brendan T., Radia, Krupali, Zhou, J. 03 1900 (has links)
Yes / Purpose: The purpose of this study was to develop a convenient test of stereopsis in the clinic that is both robust and reliable and capable of providing a measure of variability necessary to make valid comparisons between measurements obtained at different occasions or under different conditions. Methods: Stereo acuity was measured based on principles derived from the laboratory measurement of stereopsis (i.e., staircase method). Potential premeasurement compensations are described if there is a significant degree of ocular misalignment, reduced visual acuity, or aniseikonia. Forty-six adults at McGill University, 44 adults at Auckland University, and 51 adults from the University of Bradford, with an age range of 20 to 65 years old and normal or corrected-to-normal vision participated in this study. Results: Stereo acuity within this normal population was widely distributed, with a significant percentage (28%) of the population with only coarse stereo (>300 arc seconds). Across subjects, the SD was approximately 25% of the mean. Measurements at two different times were strongly (r = 0.79) and significantly (P < 0.001) correlated, with little to no significant (P = 0.79) bias (0.01) between test and retest measures of stereopsis. Conclusions: The application enables measurements over the wide disparity range and not just at the finest disparities. In addition, it allows changes in stereopsis of the order of 1.9 to be statistically distinguished.

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