Abstract
The steady-state visual evoked potential (SSVEP) visual acuity is usually defined by extrapolating a straight line regressed through significant SSVEP amplitudes plotted versus spatial frequencies to 0 μV or a noise level floor, or the finest spatial frequency evoking a significant SSVEP. This study aimed to compare the performance of the commonly used threshold determination criteria of the extrapolation technique and the finest spatial frequency technique. Visual acuity was measured both by the Freiburg Visual Acuity Test (FrACT) and SSVEP with vertical sinusoidal reversal gratings in ten adults. The extrapolation technique including three methods of linear extrapolation to zero (C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ), linear extrapolation to noise level baseline (C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) and linear extrapolation to zero versus log spatial frequency (C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> ), and the finest spatial frequency technique with significance determination by canonical correlation analysis (CCA) and “OR”operation (C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> ) were used to determine the SSVEP visual acuity. Bland-Altman method found a pretty good agreement between the SSVEP and FrACT acuity obtained by all the four threshold estimation criteria. One-way repeated-measures ANOVA and Bonferroni post-hoc analysis found that there was no significant difference among visual acuities measured by FrACT and all the four criteria, except for the visual acuity estimated by C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> slightly higher than that of C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , demonstrating that these visual acuity estimating methods had a similar performance in evaluating the visual function. The correlation and agreement between subjective FrACT acuity and objective SSVEP acuity measured by four criteria respectively were all pretty good, demonstrating that all of these four threshold estimation criteria had a good performance in SSVEP visual acuity assessment.
Highlights
At least 2.2 billion people suffer from a vision impairment or blindness in our world with most as a result of uncorrected refractive errors and cataracts, according to the World Health Organization [1,2,3]
There was an evident peak at the target frequency of 7.5 Hz on the discrete Fourier transform (DFT) spectrum for stimulus paradigms with spatial frequency below 9.5 cpd, and there was an evident peak at the target frequency of 7.5 Hz on the canonical correlation analysis (CCA) spectrum for stimulus paradigms with spatial frequency below above 15.0 cpd
As for C1, there was a regression line between the fourth and eighth points, and the state visual evoked potential (SSVEP) visual acuity threshold for C1 was defined as the spatial frequency of the intercept corresponding to the X-axis
Summary
At least 2.2 billion people suffer from a vision impairment or blindness in our world with most as a result of uncorrected refractive errors and cataracts, according to the World Health Organization [1,2,3]. As one of the most critical parts of the diagnosis of visual disorders, visual acuity testing is traditionally based on psychophysical methods, such as the naming of Snellen letters. These tests require examinees to have adequate cognitive and communication abilities and are difficult for little children and even the mentally disabled or malingerers [4, 5]. Visual evoked potentials (VEPs) offer an optional method to assess visual acuity objectively in people with difficulties in perception and recognition, and this technique of VEP-based visual acuity assessment has been studied for about 40 years [6,7,8].
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