The influence of calibration method and eye physiology on eyetracking data quality
Nyström, Marcus LU
; Andersson, Richard
LU
; Holmqvist, Kenneth
LU
and van de Weijer, Joost
LU
(2013)
In Behavior Research Methods
45(1).
p.272-288
- Abstract
- Abstract in Undetermined
Recording eye movement data with high quality is often a prerequisite for producing valid and replicable results and for drawing well-founded conclusions about the oculomotor system. Today, many aspects of data quality are often informally discussed among researchers but are very seldom measured, quantified, and reported. Here we systematically investigated how the calibration method, aspects of participants' eye physiologies, the influences of recording time and gaze direction, and the experience of operators affect the quality of data recorded with a common tower-mounted, video-based eyetracker. We quantified accuracy, precision, and the amount of valid data, and found an increase in data quality when the... (More) - Abstract in Undetermined
Recording eye movement data with high quality is often a prerequisite for producing valid and replicable results and for drawing well-founded conclusions about the oculomotor system. Today, many aspects of data quality are often informally discussed among researchers but are very seldom measured, quantified, and reported. Here we systematically investigated how the calibration method, aspects of participants' eye physiologies, the influences of recording time and gaze direction, and the experience of operators affect the quality of data recorded with a common tower-mounted, video-based eyetracker. We quantified accuracy, precision, and the amount of valid data, and found an increase in data quality when the participant indicated that he or she was looking at a calibration target, as compared to leaving this decision to the operator or the eyetracker software. Moreover, our results provide statistical evidence of how factors such as glasses, contact lenses, eye color, eyelashes, and mascara influence data quality. This method and the results provide eye movement researchers with an understanding of what is required to record high-quality data, as well as providing manufacturers with the knowledge to build better eyetrackers. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3051373
- author
- Nyström, Marcus
LU
; Andersson, Richard
LU
; Holmqvist, Kenneth
LU
and van de Weijer, Joost
LU
- organization
- publishing date
- 2013
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Behavior Research Methods
- volume
- 45
- issue
- 1
- pages
- 272 - 288
- publisher
- Springer
- external identifiers
-
- wos:000319800900026
- scopus:84874388660
- ISSN
- 1554-3528
- DOI
- 10.3758/s13428-012-0247-4
- language
- English
- LU publication?
- yes
- id
- c993985c-8f27-4b1a-bba6-7382738e33c0 (old id 3051373)
- date added to LUP
- 2016-04-01 10:09:07
- date last changed
- 2023-01-02 01:35:34
@article{c993985c-8f27-4b1a-bba6-7382738e33c0,
abstract = {{Abstract in Undetermined<br/>Recording eye movement data with high quality is often a prerequisite for producing valid and replicable results and for drawing well-founded conclusions about the oculomotor system. Today, many aspects of data quality are often informally discussed among researchers but are very seldom measured, quantified, and reported. Here we systematically investigated how the calibration method, aspects of participants' eye physiologies, the influences of recording time and gaze direction, and the experience of operators affect the quality of data recorded with a common tower-mounted, video-based eyetracker. We quantified accuracy, precision, and the amount of valid data, and found an increase in data quality when the participant indicated that he or she was looking at a calibration target, as compared to leaving this decision to the operator or the eyetracker software. Moreover, our results provide statistical evidence of how factors such as glasses, contact lenses, eye color, eyelashes, and mascara influence data quality. This method and the results provide eye movement researchers with an understanding of what is required to record high-quality data, as well as providing manufacturers with the knowledge to build better eyetrackers.}},
author = {{Nyström, Marcus and Andersson, Richard and Holmqvist, Kenneth and van de Weijer, Joost}},
issn = {{1554-3528}},
language = {{eng}},
number = {{1}},
pages = {{272--288}},
publisher = {{Springer}},
series = {{Behavior Research Methods}},
title = {{The influence of calibration method and eye physiology on eyetracking data quality}},
url = {{http://dx.doi.org/10.3758/s13428-012-0247-4}},
doi = {{10.3758/s13428-012-0247-4}},
volume = {{45}},
year = {{2013}},
}