The purpose of this study was to compare saccade detection characteristics in two mobile eye trackers with different sampling rates in a natural task. Gaze data of 11 participants were recorded in one 60 Hz and one 120 Hz mobile eye tracker and compared directly to the saccades detected by a 1000 HZ stationary tracker while a reading task was performed. Saccades and fixations were detected using a velocity based algorithm and their properties analyzed. Results showed that there was no significant difference in the number of detected fixations but mean fixation durations differed between the 60 Hz mobile and the stationary eye tracker. The 120 Hz mobile eye tracker showed a significant increase in the detection rate of saccades and an improved estimation of the mean saccade duration, compared to the 60 Hz eye tracker. To conclude, for the detection and analysis of fast eye movements, such as saccades, it is better to use a 120 Hz mobile eye tracker.

Purpose: To investigate the inter-device agreement and mean differences between a newly developed digital phoropter and the two standard methods (trial frame and manual phoropter). Methods: Refractive errors of two groups of participants were measured by two examiners (examiner 1 (E1): 36 subjects; examiner 2 (E2): 38 subjects). Refractive errors were assessed using a trial frame, a manual phoropter and a digital phoropter. Inter-device agreement regarding the measurement of refractive errors was analyzed for differences in terms of the power vector components (spherical equivalent (SE) and the cylindrical power vector components J0 and J45) between the used methods. Intraclass correlation coefficients (ICC’s) were calculated to evaluate correlations between the used methods. Results: Analyzing the variances between the three methods for SE, J0 and J45 using a two-way ANOVA showed no significant differences between the methods (SE: p = 0.13, J0: p = 0.58 and J45: p = 0.96) for examiner 1 and for examiner 2 (SE: p = 0.88, J0: p = 0.95 and J45: p = 1). Mean differences and ±95% Limits of Agreement for each pair of inter-device agreement regarding the SE for both examiners were as follows: Trial frame vs. digital phoropter: +0.10 D ± 0.56 D (E1) and +0.19 D ± 0.60 D (E2), manual phoropter vs. trial frame: −0.04 D ± 0.59 D (E1) and −0.12 D ± 0.49 D (E2) and for manual vs. digital phoropter: +0.06 D ± 0.65 D (E1) and +0.08 D ± 0.45 D (E2). ICCs revealed high correlations between all methods for both examiner (p < 0.001). The time to assess the subjective refraction was significantly smaller with the digital phoropter (examiner 1: p < 0.001; examiner 2: p < 0.001). Conclusion: “All used subjective methods show a good agreement between each other terms of ICC (>0.9). Assessing refractive errors using different subjective methods, results in similar mean differences and 95% limits of agreement, when compared to those reported in studies comparing subjective refraction non-cylcoplegic retinoscopy or autorefraction”.

Attempts to accurately predict the depth of focus (DoF) based on objective metrics have failed so far. We investigated the effect of the individual neural transfer function (iNTF) on the quality of the prediction of the subjective DoF from objective wavefront measures. Subjective DoF was assessed in 22 participants using subjective through focus curves of visual acuity (VA). Objective defocus curves were calculated for visual Strehl metrics of the optical (VSOTFa) and the modulation transfer function as well as the point spread function. DoF was computed for residual lower order aberrations (rLoA) and incorporation of iNTF. Correlations between subjective and objective DoF did not reach significance, when a) standard metrics were used and b) rLoA were considered (r _max = 0.33, p _all > 0.05). By incorporating the iNTF of the individuals in the calculation of the objective DoF from the VSOTFa metric, a moderate statistically significant correlation was found (r = 0.43, p < 0.01, Pearson). The iNTF of the individual’s eye is fundamental for the prediction of subjective DoF using the VSOTFa metric. Individualized predictions could aid future application in the correction of refractive errors like presbyopia using intraocular lenses.

Inherent distortions affect the spatial geometry of optical coherence tomography (OCT) images and consequently the foveal pit dimensions. Distortion correction provides an accurate anatomical representation of the retinal shape. A novel approach that automatically extracts foveal pit metrics from distortion-corrected OCT images using a sum of Gaussian function is presented. Foveal width, depth and slope were determined in 292 eyes with low fitting errors and high repeatability. Comparisons to undistorted scans revealed significant differences. To conclude, the internal OCT distortions affect the measurements of the foveal pit with their correction providing further insights into the role of foveal morphology in retinal pathologies and refractive development.