Literature DB >> 28879442

Comparing eye trackers by correlating their eye-metric data.

Johannes Titz1, Agnes Scholz2, Peter Sedlmeier3.   

Abstract

Up to now, the potential of eye tracking in science as well as in everyday life has not been fully realized because of the high acquisition cost of trackers. Recently, manufacturers have introduced low-cost devices, preparing the way for wider use of this underutilized technology. As soon as scientists show independently of the manufacturers that low-cost devices are accurate enough for application and research, the real advent of eye trackers will have arrived. To facilitate this development, we propose a simple approach for comparing two eye trackers by adopting a method that psychologists have been practicing in diagnostics for decades: correlating constructs to show reliability and validity. In a laboratory study, we ran the newer, low-cost EyeTribe eye tracker and an established SensoMotoric Instruments eye tracker at the same time, positioning one above the other. This design allowed us to directly correlate the eye-tracking metrics of the two devices over time. The experiment was embedded in a research project on memory where 26 participants viewed pictures or words and had to make cognitive judgments afterwards. The outputs of both trackers, that is, the pupil size and point of regard, were highly correlated, as estimated in a mixed effects model. Furthermore, calibration quality explained a substantial amount of individual differences for gaze, but not pupil size. Since data quality is not compromised, we conclude that low-cost eye trackers, in many cases, may be reliable alternatives to established devices.

Entities:  

Keywords:  Eye tracking; Low cost; Pupil size

Mesh:

Year:  2018        PMID: 28879442     DOI: 10.3758/s13428-017-0954-y

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  5 in total

1.  Visual attention to blu's parody warnings and the FDA's warning on e-cigarette advertisements.

Authors:  Brittney Keller-Hamilton; Makala Fioritto; Elizabeth G Klein; Marielle C Brinkman; Michael L Pennell; Paul Nini; Joanne G Patterson; Amy K Ferketich
Journal:  Addict Behav       Date:  2021-10-30       Impact factor: 3.913

2.  Enhancing the Sense of Attention from an Assistance Mobile Robot by Improving Eye-Gaze Contact from Its Iconic Face Displayed on a Flat Screen.

Authors:  Elena Rubies; Jordi Palacín; Eduard Clotet
Journal:  Sensors (Basel)       Date:  2022-06-04       Impact factor: 3.847

3.  Improving eye-tracking calibration accuracy using symbolic regression.

Authors:  Almoctar Hassoumi; Vsevolod Peysakhovich; Christophe Hurter
Journal:  PLoS One       Date:  2019-03-15       Impact factor: 3.240

4.  Measurement of Sexual Interests with Pupillary Responses: A Meta-Analysis.

Authors:  Janice Attard-Johnson; Martin R Vasilev; Caoilte Ó Ciardha; Markus Bindemann; Kelly M Babchishin
Journal:  Arch Sex Behav       Date:  2021-09-23

5.  PupilEXT: Flexible Open-Source Platform for High-Resolution Pupillometry in Vision Research.

Authors:  Babak Zandi; Moritz Lode; Alexander Herzog; Georgios Sakas; Tran Quoc Khanh
Journal:  Front Neurosci       Date:  2021-06-18       Impact factor: 4.677

  5 in total

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