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New Horizons and Recent Advances in Eye-Tracking Technology
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New Horizons and Recent Advances in Eye-Tracking Technology

A special issue of Journal of Eye Movement Research (ISSN 1995-8692).

Deadline for manuscript submissions: closed (20 December 2025) | Viewed by 4378

Special Issue Editor

Dr. Lee Friedman

E-Mail Website
Guest Editor
Department of Computer Science, Texas State University, 601 University Dr, San Marcos, TX 78666, USA
Interests: accuracy; precision; machine learning; virtual reality; mobile devices; wearable devices

Special Issue Information

Dear Colleagues,

This Special Issue will address current advances in eye-tracking technology.

Topics include the following:

(1) Enhanced Accuracy and Precision:

Recent breakthroughs, such as the use of deflectometry for detailed eye surface mapping, are significantly improving the accuracy of gaze direction measurement.

(2) Integration with Advanced Technologies:

Eye-tracking is being effectively integrated with technologies like Machine Learning (ML) and Virtual Reality (VR), leading to more precise diagnostics and enhanced user experiences.

(3) Accessibility and Usability:

Innovations are making eye-tracking more accessible and easier to use. This includes non-invasive systems and the ability to utilize built-in cameras on mobile devices for eye-tracking.

(4) Real-world Applications:

Wearable and mobile eye-tracking devices are enabling research and applications in real-world settings, such as assessing gait and visual exploration during walking in patients with Parkinson's disease.

Dr. Lee Friedman
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Eye Movement Research is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • accuracy
  • precision
  • machine learning
  • virtual reality
  • mobile devices
  • wearable devices

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  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

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18 pages, 822 KB  
Article
Comparing Eye-Tracking Metrics with the Driver Activity Load Index
by Julia Bend, Markus Gödker, Elise Sophie Banach and Thomas Franke
J. Eye Mov. Res. 2026, 19(2), 28; https://doi.org/10.3390/jemr19020028 - 5 Mar 2026
Viewed by 667
Abstract
This study investigated how perceptual workload in driving situations is captured by subjective ratings versus eye-tracking metrics. Fifty participants completed low- and high-complexity conditions while fixation behavior, blinks, and pupil diameter were recorded, and workload was assessed using the DALI scale. High-load scenes [...] Read more.
This study investigated how perceptual workload in driving situations is captured by subjective ratings versus eye-tracking metrics. Fifty participants completed low- and high-complexity conditions while fixation behavior, blinks, and pupil diameter were recorded, and workload was assessed using the DALI scale. High-load scenes elicited longer fixations, fewer fixations per minute, reduced blinking, and increased pupil dilation, indicating elevated attentional demand. DALI scores increased with scene complexity and were negatively associated with fixation duration, demonstrating that participants’ subjective ratings were driven primarily by perceptual strain rather than cognitive effort. Eye-tracking patterns supported this interpretation: fixation-based indicators tent to reflect the cognitive component of demand, whereas DALI selectively tracked perceptual overload. Together, these results show that DALI is highly sensitive to visual density, and that eye-movement measures provide converging evidence for its specificity as a perceptual load instrument. Full article
(This article belongs to the Special Issue New Horizons and Recent Advances in Eye-Tracking Technology)
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16 pages, 2918 KB  
Article
Analysis of Saccade Characteristics During Fusional Vergence Tests in Normal Binocular Vision Participants
by Cristina Rovira-Gay, Clara Mestre, Marc Argilés and Jaume Pujol
J. Eye Mov. Res. 2026, 19(1), 15; https://doi.org/10.3390/jemr19010015 - 3 Feb 2026
Viewed by 583
Abstract
The purpose of the study was to analyze, characterize, and compare the measurements of saccades that occurred during the positive and negative fusional vergence test (PFV and NFV, respectively) as a function of the disparity vergence demand. Thirty-four participants’ PFV and NFV amplitudes [...] Read more.
The purpose of the study was to analyze, characterize, and compare the measurements of saccades that occurred during the positive and negative fusional vergence test (PFV and NFV, respectively) as a function of the disparity vergence demand. Thirty-four participants’ PFV and NFV amplitudes were measured in a haploscopic setup, recording eye movements with an Eyelink 1000 Plus (SR Research). The visual stimulus was a column of letters. Break and recovery points were determined objectively offline, and saccades were detected with a velocity-threshold-based method. A total of 13,103 and 14,381 saccades were detected during the measurement of the PFV and NFV ranges, respectively. Saccades followed the main sequence (ρ = 0.97, p < 0.001). The distributions of saccadic amplitudes during PFV and NFV differed significantly (U = 4.28, p < 0.001). The amplitude of saccades that occurred while fusion was maintained (median (IQR) 0.73 (0.92) deg) was significantly smaller than that of saccades during diplopia (2.10 (3.90) deg) (U = −75.63, p < 0.001). The distributions of saccade direction during the measurement of PFV and NFV amplitudes were statistically significantly different (p < 0.01). These findings contribute to a better understanding of how the visual system adjusts saccades in response to different disparity vergence demand during fusional vergence amplitudes evaluation. Full article
(This article belongs to the Special Issue New Horizons and Recent Advances in Eye-Tracking Technology)
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10 pages, 566 KB  
Article
Recovery of the Pupillary Response After Light Adaptation Is Slowed in Patients with Age-Related Macular Degeneration
by Javier Barranco Garcia, Thomas Ferrazzini, Ana Coito, Dominik Brügger and Mathias Abegg
J. Eye Mov. Res. 2025, 18(6), 66; https://doi.org/10.3390/jemr18060066 - 10 Nov 2025
Viewed by 1157
Abstract
Purpose: This study evaluates a novel, non-invasive method using a virtual reality (VR) headset with integrated eye trackers to assess retinal function by measuring the recovery of the pupillary response after light adaptation in patients with age-related macular degeneration (AMD). Methods: In this [...] Read more.
Purpose: This study evaluates a novel, non-invasive method using a virtual reality (VR) headset with integrated eye trackers to assess retinal function by measuring the recovery of the pupillary response after light adaptation in patients with age-related macular degeneration (AMD). Methods: In this pilot study, fourteen patients with clinically confirmed AMD and 14 age-matched healthy controls were exposed to alternating bright and dark stimuli using a VR headset. The dark stimulus duration increased incrementally by 100 milliseconds per trial, repeated over 50 cycles. The pupillary response to the re-onset of brightness was recorded. Data were analyzed using a linear mixed-effects model to compare recovery patterns between groups and a convolutional neural network to evaluate diagnostic accuracy. Results: The pupillary response amplitude increased with longer dark stimuli, i.e., the longer the eye was exposed to darkness the bigger was the subsequent pupillary amplitude. This pupillary recovery was significantly slowed by age and by the presence of macular degeneration. Test diagnostic accuracy for AMD was approximately 92%, with a sensitivity of 90% and a specificity of 70%. Conclusions: This proof-of-concept study demonstrates that consumer-grade VR headsets with integrated eye tracking can detect retinal dysfunction associated with AMD. The method offers a fast, accessible, and potentially scalable approach for retinal disease screening and monitoring. Further optimization and validation in larger cohorts are needed to confirm its clinical utility. Full article
(This article belongs to the Special Issue New Horizons and Recent Advances in Eye-Tracking Technology)
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Review

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21 pages, 1923 KB  
Review
Mapping Eye-Tracking Research in Human–Computer Interaction: A Science-Mapping and Content-Analysis Study
by Adem Korkmaz
J. Eye Mov. Res. 2026, 19(1), 23; https://doi.org/10.3390/jemr19010023 - 12 Feb 2026
Viewed by 1184
Abstract
Eye tracking has become a central method in human–computer interaction (HCI), supported by advances in sensing technologies and AI-based gaze analysis. Despite this rapid growth, a comprehensive and up-to-date overview of eye-tracking research across the broader HCI landscape remains lacking. This study combines [...] Read more.
Eye tracking has become a central method in human–computer interaction (HCI), supported by advances in sensing technologies and AI-based gaze analysis. Despite this rapid growth, a comprehensive and up-to-date overview of eye-tracking research across the broader HCI landscape remains lacking. This study combines records from Web of Science (WoS) and Scopus to analyse 1033 publications on eye tracking in HCI published between 2020 and 2025. After merging and deduplicating the datasets, we conducted bibliometric network analyses (keyword co-occurrence, co-citation, co-authorship, and source mapping) using VOSviewer and performed a qualitative content analysis of the 50 most-cited papers. The literature is dominated by journal articles and conference papers produced by small- to medium-sized research teams (mean: 3.9 authors per paper; h-index: 29). Keyword and overlay visualisations reveal four principal research axes: deep-learning-based gaze estimation; XR-related interaction paradigms within HCI; cognitive load and human factors; and usability- and accessibility-oriented interface design. The most-cited studies focus on gaze interaction in immersive environments, deep learning for gaze estimation, multimodal interaction, and physiological approaches to assessing cognitive load. Overall, the findings indicate that eye tracking in HCI is evolving from a measurement-oriented technique into a core enabling technology that supports interaction design, cognitive assessment, accessibility, and ethical considerations such as privacy. This review identifies research gaps and outlines future directions for benchmarking practices, real-world deployments, and privacy-preserving gaze analytics in HCI. Full article
(This article belongs to the Special Issue New Horizons and Recent Advances in Eye-Tracking Technology)
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