An automated segmentation approach to calibrating infantile nystagmus waveforms

Eyetracking-enhanced VEP for nystagmus

Visual evoked potentials (VEPs) are an important prognostic indicator of visual ability in patients with nystagmus. However, VEP testing requires stable fixation, which is impossible with nystagmus. Fixation instability reduces VEP amplitude, and VEP reliability is therefore low in this important patient group. We investigated whether VEP amplitude can be increased using an eye tracker by triggering acquisition only during slow periods of the waveform. Data were collected from 10 individuals with early-onset nystagmus. VEP was obtained under continuous (standard) acquisition, or triggered during periods of low eye velocity, as detected by an eye tracker. VEP amplitude was compared using Bonferroni corrected paired samples t-tests. VEP amplitude is significantly increased when triggered during low eye velocity (95% CI 1.42-6.83 µV, t(15) = 3.25, p = 0.0053). This study provides proof-of-concept that VEP amplitude (and therefore prognostic reliability) can be increased in patients with early onset nystagmus by connecting an eye tracker and triggering acquisition during periods of lower eye velocity.

Eye Tracking to Assess the Functional Consequences of Vision Impairment: A Systematic Review

BACKGROUND

Eye tracking is a promising method for objectively assessing functional visual capabilities, but its suitability remains unclear when assessing the vision of people with vision impairment. In particular, accurate eye tracking typically relies on a stable and reliable image of the pupil and cornea, which may be compromised by abnormalities associated with vision impairment (e.g., nystagmus, aniridia).

OBJECTIVES

This study aimed to establish the degree to which video-based eye tracking can be used to assess visual function in the presence of vision impairment.

DATA SOURCES

A systematic review was conducted using PubMed, EMBASE, and Web of Science databases, encompassing literature from inception to July 2022.

STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTIONS

Studies included in the review used video-based eye tracking, included individuals with vision impairment, and used screen-based tasks unrelated to practiced skills such as reading or driving.

STUDY APPRAISAL AND SYNTHESIS METHODS

The included studies were assessed for quality using the Strengthening the Reporting of Observational Studies in Epidemiology assessment tool. Data extraction and synthesis were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

RESULTS

Our analysis revealed that five common tests of visual function were used: (i) fixation stability, (ii) smooth pursuit, (iii) saccades, (iv) free viewing, and (v) visual search. The studies reported considerable success when testing individuals with vision impairment, yielding usable data from 96.5% of participants.

LIMITATIONS

There was an overrepresentation of conditions affecting the optic nerve or macula and an underrepresentation of conditions affecting the anterior segment or peripheral retina.

CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

The results offer promise for the use of eye tracking to assess the visual function of a considerable proportion of those with vision impairment. Based on the findings, we outline a framework for how eye tracking can be used to test visual function in the presence of vision impairment.

Eye tracking: empirical foundations for a minimal reporting guideline

In this paper, we present a review of how the various aspects of any study using an eye tracker (such as the instrument, methodology, environment, participant, etc.) affect the quality of the recorded eye-tracking data and the obtained eye-movement and gaze measures. We take this review to represent the empirical foundation for reporting guidelines of any study involving an eye tracker. We compare this empirical foundation to five existing reporting guidelines and to a database of 207 published eye-tracking studies. We find that reporting guidelines vary substantially and do not match with actual reporting practices. We end by deriving a minimal, flexible reporting guideline based on empirical research (Section "An empirically based minimal reporting guideline").

Automated nystagmus detection: Accuracy of slow-phase and quick-phase algorithms to determine the presence of nystagmus

PURPOSE

To verify the accuracy of automated nystagmus detection algorithms.

METHOD

Video-oculography (VOG) plots were analyzed from consecutive patients with dizziness presenting to a neurology clinic. Data were recorded for 30 s in upright position with fixation block. For automated nystagmus detection, slow-phase algorithm parameters included mean and median slow-phase velocity (SPV), and slow-phase duration ratio. Quick-phase algorithm parameters included saccadic difference and saccadic ratio. For verification, two independent blinded assessors reviewed VOG traces and videos and coded presence or absence of nystagmus. Assessor consensus was used as reference standard. Accuracy of slow-phase and quick-phase algorithm parameters were compared, and ROC analysis was performed.

RESULTS

Among 524 analyzed VOG traces, 99 were verified as nystagmus present and 425 were verified as nystagmus absent. Prevalence of nystagmus in the sample population was 18.9%. In ROC analysis, areas under the curve of individual algorithm parameters were 0.791-0.896. With optimal thresholds for determining presence or absence of nystagmus, algorithm sensitivity (70.7-87.9%), specificity (71.8-84.0%), and negative predictive value (91.7-96.4%) were ideal, but positive predictive value (38.8-53.4%) was not ideal. Combining algorithm parameters using logistic regression models mildly improved detection accuracy.

CONCLUSION

Both slow-phase and fast-phase algorithms were accurate for detecting nystagmus. Due to low positive predictive value, the utility of independent automated nystagmus detection systems is limited in clinical settings with low prevalence of nystagmus. Combining parameters using logistic regression models appears to improve detection accuracy, indicating that machine learning may potentially optimize the accuracy of future automated nystagmus detection systems.

Eye movements elevate crowding in idiopathic infantile nystagmus syndrome

Idiopathic infantile nystagmus syndrome is a disorder characterised by involuntary eye movements, which leads to decreased acuity and visual function. One such function is visual crowding – a process whereby objects that are easily recognised in isolation become impaired by nearby flankers. Crowding typically occurs in the peripheral visual field, although elevations in foveal vision have been reported in congenital nystagmus, similar to those found with amblyopia. Here, we examine whether elevated foveal crowding with nystagmus is driven by similar mechanisms to those of amblyopia – long-term neural changes associated with a sensory deficit – or by the momentary displacement of the stimulus through nystagmus eye movements. A Landolt-C orientation identification task was used to measure threshold gap sizes with and without either horizontally or vertically placed Landolt-C flankers. We assume that a sensory deficit should give equivalent crowding in these two dimensions, whereas an origin in eye movements should give stronger crowding with horizontal flankers given the predominantly horizontal eye movements of nystagmus. We observe elevations in nystagmic crowding that are above crowding in typical vision but below that of amblyopia. Consistent with an origin in eye movements, elevations were stronger with horizontal than vertical flankers in nystagmus, but not in typical or amblyopic vision. We further demonstrate the same horizontal elongation in typical vision with stimulus movement that simulates nystagmus. Consequently, we propose that the origin of nystagmic crowding lies in the eye movements, either through image smear of the target and flanker elements or through relocation of the stimulus into the peripheral retina.

Analysing nystagmus waveforms: a computational framework

We present a new computational approach to analyse nystagmus waveforms. Our framework is designed to fully characterise the state of the nystagmus, aid clinical diagnosis and to quantify the dynamical changes in the oscillations over time. Both linear and nonlinear analyses of time series were used to determine the regularity and complexity of a specific homogenous phenotype of nystagmus. Two-dimensional binocular eye movement recordings were carried out on 5 adult subjects who exhibited a unilateral, uniplanar, vertical nystagmus secondary to a monocular late-onset severe visual loss in the oscillating eye (the Heimann-Bielschowsky Phenomenon). The non-affected eye held a central gaze in both horizontal and vertical planes (± 10 min. of arc). All affected eyes exhibited vertical oscillations, with mean amplitudes and frequencies ranging from 2.0°-4.0° to 0.25-1.5 Hz, respectively. Unstable periodic orbit analysis revealed only 1 subject exhibited a periodic oscillation. The remaining subjects were found to display quasiperiodic (n = 1) and nonperiodic (n = 3) oscillations. Phase space reconstruction allowed attractor identification and the computation of a time series complexity measure-the permutation entropy. The entropy measure was found to be able to distinguish between a periodic oscillation associated with a limit cycle attractor, a quasiperiodic oscillation associated with a torus attractor and nonperiodic oscillations associated with higher-dimensional attractors. Importantly, the permutation entropy was able to rank the oscillations, thereby providing an objective index of nystagmus complexity (range 0.15-0.21) that could not be obtained via unstable periodic orbit analysis or attractor identification alone. These results suggest that our framework provides a comprehensive methodology for characterising nystagmus, aiding differential diagnosis and also permitting investigation of the waveforms over time, thereby facilitating the quantification of future therapeutic managements. In addition, permutation entropy could provide an additional tool for future oculomotor modelling.

Successful visually guided eye movements following sight restoration after congenital cataracts

Sensitive periods have previously been identified for several human visual system functions. Yet, it is unknown to what degree the development of visually guided oculomotor control depends on early visual experience-for example, whether and to what degree humans whose sight was restored after a transient period of congenital visual deprivation are able to conduct visually guided eye movements. In the present study, we developed new calibration and analysis techniques for eye tracking data contaminated with pervasive nystagmus, which is typical for this population. We investigated visually guided eye movements in sight recovery individuals with long periods of visual pattern deprivation (3-36 years) following birth due to congenital, dense, total, bilateral cataracts. As controls we assessed (1) individuals with nystagmus due to causes other than cataracts, (2) individuals with developmental cataracts after cataract removal, and (3) individuals with normal vision. Congenital cataract reversal individuals were able to perform visually guided gaze shifts, even when their blindness had lasted for decades. The typical extensive nystagmus of this group distorted eye movement trajectories, but measures of latency and accuracy were as expected from their prevailing nystagmus-that is, not worse than in the nystagmus control group. To the best of our knowledge, the present quantitative study is the first to investigate the characteristics of oculomotor control in congenital cataract reversal individuals, and it indicates a remarkable effectiveness of visually guided eye movements despite long-lasting periods of visual deprivation.

Two-Dimensional Analysis of Horizontal and Vertical Pursuit in Infantile Nystagmus Reveals Quantitative Deficits in Accuracy and Precision

Purpose

Infantile nystagmus (IN) presents with continuous, predominantly horizontal eye oscillations. It remains controversial whether those with IN have normal horizontal pursuit, while vertical pursuit has rarely been studied. We examined whether there are pursuit deficits associated with IN by investigating the effect of target direction, velocity, and amplitude.

Methods

Twelve adults with idiopathic IN performed a pursuit task, a 0.4° dot moved either horizontally or vertically at 8 or 16°/s, through amplitudes of 8°, 16°, or 32°. Accuracy and precision errors were computed as bivariate probability density functions of target-relative eye velocities.

Results

Eye velocity was less precise along the horizontal axis during both horizontal and vertical pursuit, reflecting the primary axis of the eye oscillation. Mean accuracy error along the target trajectory during vertical pursuit was just as impaired as during horizontal pursuit. There was a greater error in accuracy along the target trajectory for 16°/s targets than 8°/s. Finally, targets that oscillated at 2.0 Hz had a greater error in accuracy along the target trajectory than frequencies of 1.0 Hz or 0.5 Hz. When studied using the same experimental protocol, pursuit performance for typical observers was always better.

Conclusions

These findings strongly support our hypothesis of severe deficits in pursuit accuracy in observers with IN for horizontally and vertically moving targets, as well as for targets that move at higher speeds or oscillate more quickly. Overall, IN pursuit impairment appears to have previously been underestimated, highlighting a need for further quantitative studies of dynamic visual function in those with IN.

A robust method for calibration of eye tracking data recorded during nystagmus

Eye tracking is a useful tool when studying the oscillatory eye movements associated with nystagmus. However, this oscillatory nature of nystagmus is problematic during calibration since it introduces uncertainty about where the person is actually looking. This renders comparisons between separate recordings unreliable. Still, the influence of the calibration protocol on eye movement data from people with nystagmus has not been thoroughly investigated. In this work, we propose a calibration method using Procrustes analysis in combination with an outlier correction algorithm, which is based on a model of the calibration data and on the geometry of the experimental setup. The proposed method is compared to previously used calibration polynomials in terms of accuracy, calibration plane distortion and waveform robustness. Six recordings of calibration data, validation data and optokinetic nystagmus data from people with nystagmus and seven recordings from a control group were included in the study. Fixation errors during the recording of calibration data from the healthy participants were introduced, simulating fixation errors caused by the oscillatory movements found in nystagmus data. The outlier correction algorithm improved the accuracy for all tested calibration methods. The accuracy and calibration plane distortion performance of the Procrustes analysis calibration method were similar to the top performing mapping functions for the simulated fixation errors. The performance in terms of waveform robustness was superior for the Procrustes analysis calibration compared to the other calibration methods. The overall performance of the Procrustes calibration methods was best for the datasets containing errors during the calibration.