GlassesValidator : A data quality tool for eye tracking glasses
(2024) In Behavior Research Methods 56(3). p.1476-1484- 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.... (More)
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.
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- author
- Niehorster, Diederick C LU ; Hessels, Roy S ; Benjamins, Jeroen S ; Nyström, Marcus LU and Hooge, Ignace T C LU
- organization
- publishing date
- 2024
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Eye tracking, Data quality, Calibration, Validation, Accuracy, Reporting practices
- in
- Behavior Research Methods
- volume
- 56
- issue
- 3
- pages
- 9 pages
- publisher
- Springer
- external identifiers
-
- scopus:85161964421
- pmid:37326770
- ISSN
- 1554-3528
- DOI
- 10.3758/s13428-023-02105-5
- language
- English
- LU publication?
- yes
- additional info
- © 2023. The Author(s).
- id
- 05f60df8-d808-4c82-9f6c-86f28c007fba
- date added to LUP
- 2023-06-23 07:38:56
- date last changed
- 2024-12-15 23:44:03
@article{05f60df8-d808-4c82-9f6c-86f28c007fba, abstract = {{<p>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.</p>}}, author = {{Niehorster, Diederick C and Hessels, Roy S and Benjamins, Jeroen S and Nyström, Marcus and Hooge, Ignace T C}}, issn = {{1554-3528}}, keywords = {{Eye tracking; Data quality; Calibration; Validation; Accuracy; Reporting practices}}, language = {{eng}}, number = {{3}}, pages = {{1476--1484}}, publisher = {{Springer}}, series = {{Behavior Research Methods}}, title = {{GlassesValidator : A data quality tool for eye tracking glasses}}, url = {{http://dx.doi.org/10.3758/s13428-023-02105-5}}, doi = {{10.3758/s13428-023-02105-5}}, volume = {{56}}, year = {{2024}}, }