ArticlePsychology & neuroscience2023
Evaluation of Gaze-to-Object Mapping Algorithms for Use in "Real-World" Translatable Neuropsychological Paradigms.
Article in Psychology & neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Attentional Bias During a Novel Alcohol Cue Virtual Reality Paradigm.Alcohol, clinical & experimental research · 2026Article
- Attentional Bias, Pupillometry, and Spontaneous Blink Rate: Eye Characteristic Assessment Within a Translatable Nicotine Cue Virtual Reality Paradigm.JMIR serious games · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Objective: Eye-tracking technology is commonly used for identifying objects of visual attention. However, applying this technology to virtual reality (VR) applications is challenging. This report analyzes the performance of two gaze-to-object mapping (GTOM) algorithms applied to eye-gaze data acquired during a "real-world" VR cue-reactivity paradigm. Methods: Two groups of participants completed a VR paradigm using an HTC Vive Pro Eye. The gazed objects were determined by the reported gaze rays and one of two GTOM algorithms - naïve ray-casting (n=18) or a combination of ray-casting and Tobii's G2OM algorithm (n=18). Percent gaze duration was calculated from 1-second intervals before each object interaction to estimate gaze accuracy. The object volume of maximal divergence between algorithms was determined by maximizing the difference in Hedge's G effect sizes between small and large percent gaze duration distributions. Differences in percent gaze duration based on algorithm and target object size were tested with a mixed ANOVA. Results: The maximum Hedge's G effect sizes differentiating large and small target objects was observed at an 800cm Conclusions: Results demonstrated that Tobii's G2OM method outperformed naïve ray-casting in this "real-world" paradigm. As both algorithms show a clear decrease in performance for detecting objects with volumes <800cm
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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.