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GlassesValidator: A data quality tool for eye tracking glasses.

Diederick C Niehorster1, Roy S Hessels2, Jeroen S Benjamins3

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Summary

This study introduces a quick validation procedure for wearable eye trackers, using a printable poster and Python software. The method accurately measures eye tracking accuracy and precision within a minute per participant.

Keywords:
AccuracyCalibrationData qualityEye trackingReporting practicesValidation

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Area of Science:

  • Ophthalmology
  • Computer Science
  • Human-Computer Interaction

Background:

  • Accurate reporting of eye tracking data is crucial, as proposed by Holmqvist et al. (2022).
  • Existing methods for determining the accuracy of wearable eye trackers are not readily accessible.
  • Wearable eye tracking technology is increasingly used in research and various applications.

Purpose of the Study:

  • To develop a simple, fast, and accessible validation procedure for assessing the accuracy of wearable eye trackers.
  • To provide researchers with a practical tool for ensuring the quality of eye tracking data.
  • To facilitate the adoption of standardized reporting guidelines for eye tracking studies.

Main Methods:

  • Development of a printable validation poster and accompanying Python software.
  • Administration of the validation procedure to 61 participants using a wearable eye tracker.
  • Testing the Python software with six different wearable eye tracker models.

Main Results:

  • The validation procedure can be completed in under a minute per participant.
  • The procedure provides reliable measures of both accuracy and precision for eye tracking data.
  • The accompanying software is user-friendly, requiring no advanced computer skills for offline data analysis.

Conclusions:

  • The developed validation procedure offers a quick and easy solution for assessing wearable eye tracker accuracy.
  • This tool supports the accurate reporting of eye tracking data, aligning with proposed minimum reporting guidelines.
  • The accessibility and ease of use of this method can improve the quality and comparability of eye tracking research.