Eye movement measures for predicting eye gaze accuracy and symptoms in 2D and 3D displays

Chiuhsiang Joe Lin*, Yogi Tri Prasetyo, Retno Widyaningrum

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Citations (Scopus)

Abstract

The current study applied Structural Equation Modeling (SEM) to analyze the interrelationship among index of difficulty (ID), environment, saccade duration (SD), revisited fixation duration (RFD), number of fixation (NF), pupil size (PS), eye gaze accuracy (AC), and symptoms simultaneously. SD, RFD, NF, PS, and AC were measured by utilizing the Tobii eye tracker system. Twelve participants were recruited to perform multi-directional tapping task using within-subject design with two different environments (2D screen display and 3D stereoscopic display) and six different levels of ID. SEM showed that ID had significant direct effects on SD and RFD while environment was found had significant direct effects on SD, RFD, PS, AC, and symptoms. Among selected eye movement measures, NF was found to be the best predictor of AC and PS was found to be the best predictor of symptoms. In addition, RFD was also found to be a good predictor of symptoms. Our results found that higher AC was achieved by projecting the image in the 2D screen display with higher ID and it resulted in higher SD and higher NF. Regarding the symptoms, our results found that lower symptoms were achieved by projecting the image in the 2D screen display with lower ID and it resulted in lower PS, and lower RFD. Practitioner Summary: The SEM could provide valuable theoretical foundations to identify the interrelationship among eye movement measures, AC, and symptoms particularly for VR researchers and interface developers.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalDisplays
Volume60
DOIs
Publication statusPublished - Dec 2019
Externally publishedYes

Keywords

  • Eye movement
  • Stereoscopic
  • Structural equation modeling

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