TY - JOUR
T1 - Eye movement measures for predicting eye gaze accuracy and symptoms in 2D and 3D displays
AU - Lin, Chiuhsiang Joe
AU - Prasetyo, Yogi Tri
AU - Widyaningrum, Retno
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/12
Y1 - 2019/12
N2 - 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.
AB - 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.
KW - Eye movement
KW - Stereoscopic
KW - Structural equation modeling
UR - http://www.scopus.com/inward/record.url?scp=85071083446&partnerID=8YFLogxK
U2 - 10.1016/j.displa.2019.08.002
DO - 10.1016/j.displa.2019.08.002
M3 - Article
AN - SCOPUS:85071083446
SN - 0141-9382
VL - 60
SP - 1
EP - 8
JO - Displays
JF - Displays
ER -