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GlassesValidator: A data quality tool for eye tracking glasses

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

According to the proposal for a minimum reporting guideline for an eye tracking study by Holmqvist et al. (2022), the accuracy (in degrees) of eye tracking data should be reported. Currently, there is no easy way to determine accuracy for wearable eye tracking recordings. To enable determining the accuracy quickly and easily, we have produced a simple validation procedure using a printable poster and accompanying Python software. We tested the poster and procedure with 61 participants using one wearable eye tracker. In addition, the software was tested with six different wearable eye trackers. We found that the validation procedure can be administered within a minute per participant and provides measures of accuracy and precision. Calculating the eye-tracking data quality measures can be done offline on a simple computer and requires no advanced computer skills.

Original languageEnglish
Pages (from-to) 1476–1484
Number of pages9
JournalBehavior Research Methods
Volume56
Issue number3
Early online date8 Jun 2023
DOIs
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2023.

Funding

The authors thank SeeTrue Technologies Oy (Joensuu, Finland), Pupil Labs GmbH (Berlin, Germany) and Tobii Pro AB (Stockholm, Sweden) for lending us their eye trackers. The authors also thank Lund University Humanities Lab for the use of the laboratory and providing us with the SMI ETG 2.0 Glasses and the Tobii Pro Glasses 2. Author RH was supported by the Consortium on Individual Development (CID). CID is funded through the Gravitation program of the Dutch Ministry of Education, Culture, and Science and the NWO (Grant No. 024.001.003).

FundersFunder number
Dutch Ministry of Education, Culture, and Science
Nederlandse Organisatie voor Wetenschappelijk Onderzoek024.001.003
Nederlandse Organisatie voor Wetenschappelijk Onderzoek

    Keywords

    • Accuracy
    • Calibration
    • Data quality
    • Eye tracking
    • Reporting practices
    • Validation

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