There is good agreement between subjective refraction and WAM-5500 measurements. In contrast, the PowerRef-II produced more hyperopic results. There were no differences among instruments at 2.50 D of static stimulation; however, differences were found at 5.00 D. In the dynamic measurements, the PowerRef-II measured faster velocities, partly attributed to the difference in the sampling frequency.
PurposeTo conduct a clinical validation of a virtual reality-based experimental system that is able to assess the spherical subjective refraction simplifying the methodology of ocular refraction.MethodsFor the agreement assessment, spherical refraction measurements were obtained from 104 eyes of 52 subjects using three different methods: subjectively with the experimental prototype (Subj.E) and the classical subjective refraction (Subj.C); and objectively with the WAM-5500 autorefractor (WAM). To evaluate precision (intra- and inter-observer variability) of each refractive tool independently, 26 eyes were measured in four occasions.ResultsWith regard to agreement, the mean difference (±SD) for the spherical equivalent (M) between the new experimental subjective method (Subj.E) and the classical subjective refraction (Subj.C) was −0.034 D (±0.454 D). The corresponding 95% Limits of Agreement (LoA) were (−0.856 D, 0.924 D). In relation to precision, intra-observer mean difference for the M component was 0.034 ± 0.195 D for the Subj.C, 0.015 ± 0.177 D for the WAM and 0.072 ± 0.197 D for the Subj.E. Inter-observer variability showed worse precision values, although still clinically valid (below 0.25 D) in all instruments.ConclusionsThe spherical equivalent obtained with the new experimental system was precise and in good agreement with the classical subjective routine. The algorithm implemented in this new system and its optical configuration has been shown to be a first valid step for spherical error correction in a semiautomated way.
Purpose To investigate a new algorithm to perform an automated non-cycloplegic refraction in adults. Methods Fifty healthy subjects were measured twice (test–retest) with the new automated subjective refraction method and with the conventional clinician subjective refraction procedure. Objective refraction was also measured with the Grand Seiko WAM-5500 autorefractor. The new automated method was inspired on the root finding bisection algorithm and on the Euclidean distances in the power vector domain. The algorithm was implemented in a computer that was synchronized with a customized motorized phoropter. Repeatability was mainly assessed with the within-subject standard deviation (Sw) and accuracy was mainly assessed with the limits of agreement. Results The within-subject standard deviations of the power vector components ( M , J0, J45) obtained for the right eye are (±0.13, ±0.04, ±0.05) D and (±0.17, ±0.03, ±0.07) D, respectively, for the clinical and the automated subjective refraction methods. The limits of agreement (with the clinical method) for the automated and the objective methods are, respectively (±0.56, ±0.18, ±0.31) D and (±0.77, ±0.15, ±0.18) D. Similar results are obtained for the left eye. Conclusions The proposed automated method is repeatable and more accurate than objective techniques in healthy adults. However, it is not accurate enough to replace the clinical subjective refraction yet and it should be tested in a wider population in terms of age, refraction and different ocular conditions. Despite these important limitations, this method has been shown to be a potentially valuable method to improve the access to primary eye care services in developing countries.
Simple color-difference formulae and pictorial images have traditionally been used to estimate the visual impact of color errors introduced by image-reproduction processes. But the limited gamut of RGB cameras constrains such analyses, particularly of natural scenes. The purpose of this work was to estimate visual sensitivity to color errors introduced deliberately into pictures synthesized from hyperspectral images of natural scenes without gamut constraints and to compare discrimination thresholds expressed in CIELAB and S-CIELAB color spaces. From each original image, a set of approximate images with variable color errors were generated and displayed on a calibrated RGB color monitor. The threshold for perceptibility of the errors was determined in a paired-comparison experiment. In agreement with previous studies, it was found that discrimination between original and approximate images needed on average a CIELAB color difference DE ab * of about 2.2. Although a large variation of performance across the nine images tested was found when errors were expressed in CIELAB units, little variation was obtained when they were expressed in S-CIELAB units.
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