ArticleSensors (Basel, Switzerland)2020
Development and Calibration of an Eye-Tracking Fixation Identification Algorithm for Immersive Virtual Reality.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- REAsmash-ET: a methodological framework for combined cognitive and motor assessment through eye-tracking and kinematic metrics in immersive VR search-and-reach task.Journal of neuroengineering and rehabilitation · 2025Trial
- Trial
- A randomised controlled test in virtual reality of the effects on paranoid thoughts of virtual humans' facial animation and expression.Scientific reports · 2024Trial
- Predictive use of environmental regularities requires action relevance.Scientific reports · 2026Article
- An EEG Dataset of Exploring Navigation in Virtual Reality.Scientific data · 2025Article
- Article
- Performance Measurement of Gesture-Based Human-Machine Interfaces Within eXtended Reality Head-Mounted Displays.Sensors (Basel, Switzerland) · 2025Article
- The fundamentals of eye tracking part 4: Tools for conducting an eye tracking study.Behavior research methods · 2025Article
- Scene semantics affects allocentric spatial coding for action in naturalistic (virtual) environments.Scientific reports · 2024Article
- Virtual reality boxing: impact of gaze-contingent blur on elite boxers performance and gaze behavior.Frontiers in sports and active living · 2024Article
- Familiarization with Mixed Reality for Individuals with Autism Spectrum Disorder: An Eye Tracking Study.Sensors (Basel, Switzerland) · 2023Article
- Eye movement characteristics in a mental rotation task presented in virtual reality.Frontiers in neuroscience · 2023Article
- Virtual reality boxing: Gaze-contingent manipulation of stimulus properties using blur.Frontiers in psychology · 2022Article
- Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store.Frontiers in psychology · 2022Article
- Gaze Behavior Effect on Gaze Data Visualization at Different Abstraction Levels.Sensors (Basel, Switzerland) · 2021Article
- ARETT: Augmented Reality Eye Tracking Toolkit for Head Mounted Displays.Sensors (Basel, Switzerland) · 2021Article
- Hands-Free User Interface for VR Headsets Based on In Situ Facial Gesture Sensing.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fixation identification is an essential task in the extraction of relevant information from gaze patterns; various algorithms are used in the identification process. However, the thresholds used in the algorithms greatly affect their sensitivity. Moreover, the application of these algorithm to eye-tracking technologies integrated into head-mounted displays, where the subject's head position is unrestricted, is still an open issue. Therefore, the adaptation of eye-tracking algorithms and their thresholds to immersive virtual reality frameworks needs to be validated. This study presents the development of a dispersion-threshold identification algorithm applied to data obtained from an eye-tracking system integrated into a head-mounted display. Rules-based criteria are proposed to calibrate the thresholds of the algorithm through different features, such as number of fixations and the percentage of points which belong to a fixation. The results show that distance-dispersion thresholds between 1-1.6° and time windows between 0.25-0.4 s are the acceptable range parameters, with 1° and 0.25 s being the optimum. The work presents a calibrated algorithm to be applied in future experiments with eye-tracking integrated into head-mounted displays and guidelines for calibrating fixation identification algorithms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.