Assessment of eye fatigue caused by 3D displays based on multimodal measurements

• Published in: Sensors (Basel, Switzerland) Vol. 14; no. 9; pp. 16467 - 16485
• Main Authors: Bang, Jae Won, Heo, Hwan, Choi, Jong-Suk, Park, Kang Ryoung
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 04.09.2014; MDPI
• Subjects: 3D display; Accuracy; Adult; Asthenopia - diagnosis; Asthenopia - physiopathology; Blinking; Cameras; Data Display; Diagnostic Techniques, Ophthalmological; Electrocardiography; Electroencephalography; Electroencephalography - methods; Equipment Design; Equipment Failure Analysis; eye fatigue; Eye movements; Female; Humans; Imaging, Three-Dimensional - instrumentation; Male; Methods; multimodal measurement; remote gaze tracking system; Reproducibility of Results; Sensitivity and Specificity; Sensors; Thermography - methods
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s140916467

With the development of 3D displays, user's eye fatigue has been an important issue when viewing these displays. There have been previous studies conducted on eye fatigue related to 3D display use, however, most of these have employed a limited number of modalities for measurements, such as electroencephalograms (EEGs), biomedical signals, and eye responses. In this paper, we propose a new assessment of eye fatigue related to 3D display use based on multimodal measurements. compared to previous works Our research is novel in the following four ways: first, to enhance the accuracy of assessment of eye fatigue, we measure EEG signals, eye blinking rate (BR), facial temperature (FT), and a subjective evaluation (SE) score before and after a user watches a 3D display; second, in order to accurately measure BR in a manner that is convenient for the user, we implement a remote gaze-tracking system using a high speed (mega-pixel) camera that measures eye blinks of both eyes; thirdly, changes in the FT are measured using a remote thermal camera, which can enhance the measurement of eye fatigue, and fourth, we perform various statistical analyses to evaluate the correlation between the EEG signal, eye BR, FT, and the SE score based on the T-test, correlation matrix, and effect size. Results show that the correlation of the SE with other data (FT, BR, and EEG) is the highest, while those of the FT, BR, and EEG with other data are second, third, and fourth highest, respectively.