A study of artificial eyes for the measurement of precision in eye-trackers

• Published in: Behavior research methods Vol. 49; no. 3; pp. 947 - 959
• Main Authors: Wang, Dong, Mulvey, Fiona B., Pelz, Jeff B., Holmqvist, Kenneth
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2017; Springer Nature B.V
• Subjects: Artificial eye; Behavioral Science and Psychology; Cognitive Psychology; Complexity; Data quality; Eye; Eye movements; Eye Movements - physiology; Eye, Artificial - standards; Eye-tracker noise; Eyes & eyesight; Humans; Measurement; Physiological effects; Power-spectral density; Precision; Psychology; Psychology (excluding Applied Psychology); Psykologi; Psykologi (exklusive tillämpad psykologi); Pupil size; Samhällsvetenskap; Social Sciences; Spectral analysis; Standardization; Tracking control systems; Data quality; Eye-tracker noise; Eye movements; Power-spectral density; Precision; Artificial eye
• ISSN: 1554-3528; 1554-3528
• DOI: 10.3758/s13428-016-0755-8

The precision of an eye-tracker is critical to the correct identification of eye movements and their properties. To measure a system’s precision, artificial eyes (AEs) are often used, to exclude eye movements influencing the measurements. A possible issue, however, is that it is virtually impossible to construct AEs with sufficient complexity to fully represent the human eye. To examine the consequences of this limitation, we tested currently used AEs from three manufacturers of eye-trackers and compared them to a more complex model, using 12 commercial eye-trackers. Because precision can be measured in various ways, we compared different metrics in the spatial domain and analyzed the power-spectral densities in the frequency domain. To assess how precision measurements compare in artificial and human eyes, we also measured precision using human recordings on the same eye-trackers. Our results show that the modified eye model presented can cope with all eye-trackers tested and acts as a promising candidate for further development of a set of AEs with varying pupil size and pupil–iris contrast. The spectral analysis of both the AE and human data revealed that human eye data have different frequencies that likely reflect the physiological characteristics of human eye movements. We also report the effects of sample selection methods for precision calculations. This study is part of the EMRA/COGAIN Eye Data Quality Standardization Project.