ArticlePloS one2022
How to choose the size of facial areas of interest in interactive eye tracking.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed.
- Gaze behavior during closed-captioned movie viewing adapts to absent audio through more frequent switching between text and scene.Journal of vision · 2026Article
- FaceTrack-AOI: An AI-driven tool for automated dynamic AOI placement and eye movement analysis in face perception studies.Behavior research methods · 2026Article
- Eye-Tracked Visual Attention to Anthropomorphic Appearance and Empathic Responses in AI Medical Conversational Agents: Dissociating Trust Gains from Attentional Synergy.Journal of eye movement research · 2026Article
- The fundamentals of eye tracking part 6: Working with areas of interest.Behavior research methods · 2026Article
- Unveiling Distinctive Eye Tracking Markers to Distinguish Toddlers with High-Risk Autism as Indicated by ADOS Within an Elevated-Likelihood Toddler Sample.Children (Basel, Switzerland) · 2025Article
- The effect of pupil size on data quality in head-mounted eye trackers.Behavior research methods · 2025Article
- When is enough enough? Empirical guidelines to determine participant sample size for scene viewing studies.Behavior research methods · 2025Article
- Altered interactive dynamics of gaze behavior during face-to-face interaction in autistic individuals: a dual eye-tracking study.Molecular autism · 2025Article
- The fundamentals of eye tracking part 4: Tools for conducting an eye tracking study.Behavior research methods · 2025Article
- Eye tracker calibration: How well can humans refixate a target?Behavior research methods · 2024Article
- Social attention in the wild - fixations to the eyes and autistic traits during a naturalistic interaction in a healthy sample.Scientific reports · 2024Article
- Gaze Zone Classification for Driving Studies Using YOLOv8 Image Classification.Sensors (Basel, Switzerland) · 2024Article
- Influence of autistic traits and communication role on eye contact behavior during face-to-face interaction.Scientific reports · 2024Article
- Maximizing valid eye-tracking data in human and macaque infants by optimizing calibration and adjusting areas of interest.Behavior research methods · 2024Article
- The use of the differential outcomes procedure for the recognition of facial expressions of complex emotions and its electrophysiological correlates.Frontiers in psychology · 2024Article
- Gaze behavior in response to affect during natural social interactions.Frontiers in psychology · 2024Article
- How robust are wearable eye trackers to slow and fast head and body movements?Behavior research methods · 2023Article
- Enhancing precision in human neuroscience.eLife · 2023Review
- The robustness of individual differences in gaze preferences toward faces and eyes across face-to-face experimental designs and its relation to social anxiety.Journal of vision · 2023Article
- No evidence that gaze anxiety predicts gaze avoidance behavior during face-to-face social interaction.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer's test conditions, validation is essential with regard to the quality of gaze data and other factors potentially threatening the validity of this signal. In this study, we evaluated the impact of accuracy and areas of interest (AOIs) size on the classification of simulated gaze (fixation) data. We defined AOIs of different sizes using the Limited-Radius Voronoi-Tessellation (LRVT) method, and simulated gaze data for facial target points with varying accuracy. As hypothesized, we found that accuracy and AOI size had strong effects on gaze classification. In addition, these effects were not independent and differed in falsely classified gaze inside AOIs (Type I errors; false alarms) and falsely classified gaze outside the predefined AOIs (Type II errors; misses). Our results indicate that smaller AOIs generally minimize false classifications as long as accuracy is good enough. For studies with lower accuracy, Type II errors can still be compensated to some extent by using larger AOIs, but at the cost of more probable Type I errors. Proper estimation of accuracy is therefore essential for making informed decisions regarding the size of AOIs in eye tracking research.
Indexed as
Identifiers
What OpenQuestion holds
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.