A low-cost, high-performance video-based binocular eye tracker for psychophysical research

Quantitative Assessment of Fixational Disparity Using a Binocular Eye-Tracking Technique in Children with Strabismus

Fixational eye movements are important for holding the central visual field on a target for a specific period of time. In this study, we aimed to quantitatively assess fixational disparities using binocular eye tracking in children with strabismus (before and after surgical alignment) and healthy children. Fixational disparities in 117 children (4-18 years; 57 with strabismus and 60 age-similar healthy controls) were recorded under binocular viewing with corrected refractive errors. Disparities in gaze positions relative to the target location were recorded for both eyes. The main outcome measures included fixational disparities along horizontal and vertical axes in the fixation test. Children with strabismus exhibited significant (p < 0.001) fixational disparities compared to healthy children in both horizontal and vertical directions. Additionally, children with esotropia had poorer fixational function compared to those with exotropia. The occurrence of fixational disparities significantly decreased in the horizontal direction following strabismus surgery. A significant negative correlation was observed between binocular best-corrected visual acuity and fixational disparities in children with strabismus. Children with strabismus had significant fixational disparities that were observably diminished in the horizontal direction after surgical alignment. Binocular assessment of fixational disparities can provide a more comprehensive evaluation of visual function in individuals with strabismus.

The fundamentals of eye tracking part 4: Tools for conducting an eye tracking study

Researchers using eye tracking are heavily dependent on software and hardware tools to perform their studies, from recording eye tracking data and visualizing it, to processing and analyzing it. This article provides an overview of available tools for research using eye trackers and discusses considerations to make when choosing which tools to adopt for one's study.

Disentangling the Neural Circuits of Arousal and Anxiety-Like Behavior

Anxiety disorders are prevalent and debilitating conditions characterized by excessive concern and fear, affecting thoughts, behaviors, and sensations. A critical component of anxiety is arousal, a complex process involving alertness regulation and stimulus salience modulation. While arousal is adaptive in normal circumstances, dysregulation can lead to hypoarousal or hyperarousal, affecting response selection and threat perception. This chapter reviews challenges in studying arousal in preclinical anxiety models, emphasizing the need for multicomponent measurement and analysis. Novel methodologies integrating physiological measurement with activity tracking of neurons with single-cell resolution in awake animals are discussed, with emphasis in current challenges. Understanding these mechanisms is crucial for developing effective treatments for anxiety disorders.

Retinal "sweet spot" for myopia treatment

We studied which retinal area controls short-term axial eye shortening when human subjects were exposed to + 3.0D monocular defocus. A custom-built infrared eye tracker recorded the point of fixation while subjects watched a movie at a 2 m distance. The eye tracker software accessed each individual movie frame in real-time and covered the points of fixation in the movie with a uniform grey patch. Four patches were programmed: (1) foveal patch (0-3 degrees), (2) annular patch (3-9 deg), (3) foveal patch (0-3 deg) combined with an annular patch (6-9 deg), and (4) full-field patch where only 6-10 deg were exposed to the defocus. Axial eye shortening was elicited similarly with full-field positive defocus and with the foveal patch, indicating that the fovea made only a minor contribution (-11 ± 12 μm vs. -14 ± 17 μm, respectively, n.s.). In contrast, patching a 3-9 degrees annular area or fovea together with an annular area of 6-9 degrees, completely suppressed the effect when compared with full-field defocus (+ 3 ± 1 μm or -2 ± 13 μm vs. -11 ± 12 μm, respectively, p < 0.001). Finally, we found that the near-peripheral retina (6-10 degrees) is a "sweet spot" for positive defocus detection and alone can regulate eye growth control mechanism, and perhaps long-term refractive development (-9 ± 8 μm vs. full-field: -11 ± 12 μm, n.s.).

Open Iris - An Open Source Framework for Video-Based Eye-Tracking Research and Development

Eye-tracking is an essential tool in many fields, yet existing solutions are often limited for customized applications due to cost or lack of flexibility. We present OpenIris, an adaptable and user-friendly open-source framework for video-based eye-tracking. OpenIris is developed in C# with modular design that allows further extension and customization through plugins for different hardware systems, tracking, and calibration pipelines. It can be remotely controlled via a network interface from other devices or programs. Eye movements can be recorded online from camera stream or offline post-processing recorded videos. Example plugins have been developed to track eye motion in 3-D, including torsion. Currently implemented binocular pupil tracking pipelines can achieve frame rates of more than 500Hz. With the OpenIris framework, we aim to fill a gap in the research tools available for high-precision and high-speed eye-tracking, especially in environments that require custom solutions that are not currently well-served by commercial eye-trackers.

Precise localization of corneal reflections in eye images using deep learning trained on synthetic data

We present a deep learning method for accurately localizing the center of a single corneal reflection (CR) in an eye image. Unlike previous approaches, we use a convolutional neural network (CNN) that was trained solely using synthetic data. Using only synthetic data has the benefit of completely sidestepping the time-consuming process of manual annotation that is required for supervised training on real eye images. To systematically evaluate the accuracy of our method, we first tested it on images with synthetic CRs placed on different backgrounds and embedded in varying levels of noise. Second, we tested the method on two datasets consisting of high-quality videos captured from real eyes. Our method outperformed state-of-the-art algorithmic methods on real eye images with a 3-41.5% reduction in terms of spatial precision across data sets, and performed on par with state-of-the-art on synthetic images in terms of spatial accuracy. We conclude that our method provides a precise method for CR center localization and provides a solution to the data availability problem, which is one of the important common roadblocks in the development of deep learning models for gaze estimation. Due to the superior CR center localization and ease of application, our method has the potential to improve the accuracy and precision of CR-based eye trackers.

A review of experimental task design in psychophysical eye tracking research

While eye tracking is a technique commonly used in the experimental study of higher-level perceptual processes such as visual search, working memory, reading, and scene exploration, its use for the quantification of basic visual functions (visual acuity, contrast sensitivity, color vision, motion detection) is less explored. The use of eye movement features as dependent variables in a psychophysical investigation can serve multiple roles. They can be central in studies with neurological patients or infants that cannot comply with verbal instructions, understand task demands, and/or emit manual responses. The technique may also serve a complementary role, determining the conditions under which a manual or verbal response is given, such as stimulus position in the visual field, or it can afford the analysis of new dependent variables, such as the time interval between oculomotor and manual responses. Our objective is to review the literature that applied the eye tracking technique to psychophysical problems. The two questions our review raises are: can eye movements (reflex or voluntary) be an objective index of stimulus detection in psychophysical tasks? If so, under what conditions, and how does it compare with traditional paradigms requiring manual responses? Our (non-systematic) methodological review selected studies that used video-oculography as the technique of choice and had a basic visual function as their primary object of investigation. Studies satisfying those criteria were then categorized into four broad classes reflecting their main research interest: (1) stimulus detection and threshold estimation, (2) the effects of stimulus properties on fixational eye movements, (3) the effects of eye movements on perception, and (4) visual field assessment. The reviewed studies support the idea that eye tracking is a valuable technique for the study of basic perceptual processes. We discuss methodological characteristics within each of the proposed classification area, with the objective of informing future task design.

Spintronic Eyeblink Gesture Sensor With Wearable Interface System

This work presents an eyeblink system that detects magnets placed on the eyelid via integrated magnetic sensors and an analogue circuit on an eyewear frame (without a glass lens). The eyelid magnets were detected using tunnelling magnetoresistance (TMR) bridge sensors with a sensitivity of 14 mV/V/Oe and were positioned centre-right and centre-left of the eyewear frame. Each eye side has a single TMR sensor wired to a single circuit, where the signal was filtered (<0.5 Hz and >30 Hz) and amplified to detect the weak magnetic field produced by the 3-millimetre (mm) diameter and 0.5 mm thickness N42 Neodymium magnets attached to a medical tape strip, for the adult-age demographic. Each eyeblink was repeated by a trigger command (right eyeblink) followed by the appropriate command, right, left or both eyeblinks. The eyeblink gesture system has shown repeatability, resulting in blinking classification based on the analogue signal amplitude threshold. As a result, the signal can be scaled and classified as well as, integrated with a Bluetooth module in real-time. This will enable end-users to connect to various other Bluetooth enabled devices for wireless assistive technologies. The eyeblink system was tested by 14 participants via a stimuli-based game. Within an average time of 185-seconds, the system demonstrated a group mean accuracy of 72% for 40 commands. Moreover, the maximum information transfer rate (ITR) of the participants was 35.95 Bits per minute.

Feigned ADHD Associated Cognitive Impairment: Utility of Integrating an Eye-tracker and the MOXO-dCPT

OBJECTIVE

The current study assessed the utility of eye-movements measures, gathered while participants performed a commercially available Continuous Performance Test (CPT), to detect feigned ADHD-associated cognitive impairment.

METHOD

Healthy simulators (n = 37), ADHD patients (n = 33), and healthy controls (n = 36) performed an eye-tracker integrated MOXO-dCPT and a stand-alone validity indicator.

RESULTS

Simulators gazed significantly longer at regions that were irrelevant for successful MOXO-dCPT performance compared to ADHD patients and healthy controls. This eye-movement measure, however, had lower sensitivity than traditional MOXO-dCPT indices.

DISCUSSION

Gaze direction measures, gathered while performing a CPT, show initial promise as validity indicators. Traditional CPT measures, however, are more sensitive and therefore offer a more promising path for the establishment of CPT-based validity indicators. The current study is an initial exploration of the issue and further evaluation of both theoretical and practical aspects is mandated.

Detection of Oculomotor Dysmetria From Mobile Phone Video of the Horizontal Saccades Task Using Signal Processing and Machine Learning Approaches

Eye movement assessments have the potential to help in diagnosis and tracking of neurological disorders. Cerebellar ataxias cause profound and characteristic abnormalities in smooth pursuit, saccades, and fixation. Oculomotor dysmetria (i.e., hypermetric and hypometric saccades) is a common finding in individuals with cerebellar ataxia. In this study, we evaluated a scalable approach for detecting and quantifying oculomotor dysmetria. Eye movement data were extracted from iPhone video recordings of the horizontal saccade task (a standard clinical task in ataxia) and combined with signal processing and machine learning approaches to quantify saccade abnormalities. Entropy-based measures of eye movements during saccades were significantly different in 72 individuals with ataxia with dysmetria compared with 80 ataxia and Parkinson's participants without dysmetria. A template matching-based analysis demonstrated that saccadic eye movements in patients without dysmetria were more similar to the ideal template of saccades. A support vector machine was then used to train and test the ability of multiple signal processing features in combination to distinguish individuals with and without oculomotor dysmetria. The model achieved 78% accuracy (sensitivity= 80% and specificity= 76%). These results show that the combination of signal processing and machine learning approaches applied to iPhone video of saccades, allow for extraction of information pertaining to oculomotor dysmetria in ataxia. Overall, this inexpensive and scalable approach for capturing important oculomotor information may be a useful component of a screening tool for ataxia and could allow frequent at-home assessments of oculomotor function in natural history studies and clinical trials.

Novel Hybrid Brain-Computer Interface for Virtual Reality Applications Using Steady-State Visual-Evoked Potential-Based Brain-Computer Interface and Electrooculogram-Based Eye Tracking for Increased Information Transfer Rate

Brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have recently attracted increasing attention in virtual reality (VR) applications as a promising tool for controlling virtual objects or generating commands in a "hands-free" manner. Video-oculography (VOG) has been frequently used as a tool to improve BCI performance by identifying the gaze location on the screen, however, current VOG devices are generally too expensive to be embedded in practical low-cost VR head-mounted display (HMD) systems. In this study, we proposed a novel calibration-free hybrid BCI system combining steady-state visual-evoked potential (SSVEP)-based BCI and electrooculogram (EOG)-based eye tracking to increase the information transfer rate (ITR) of a nine-target SSVEP-based BCI in VR environment. Experiments were repeated on three different frequency configurations of pattern-reversal checkerboard stimuli arranged in a 3 × 3 matrix. When a user was staring at one of the nine visual stimuli, the column containing the target stimulus was first identified based on the user's horizontal eye movement direction (left, middle, or right) classified using horizontal EOG recorded from a pair of electrodes that can be readily incorporated with any existing VR-HMD systems. Note that the EOG can be recorded using the same amplifier for recording SSVEP, unlike the VOG system. Then, the target visual stimulus was identified among the three visual stimuli vertically arranged in the selected column using the extension of multivariate synchronization index (EMSI) algorithm, one of the widely used SSVEP detection algorithms. In our experiments with 20 participants wearing a commercial VR-HMD system, it was shown that both the accuracy and ITR of the proposed hybrid BCI were significantly increased compared to those of the traditional SSVEP-based BCI in VR environment.