Abstract
The traditional way to detect visual fatigue is to use the questionnaire or to use critical fusion frequency of high-frequency exchanges due to eye fatigue. The objective of this study was to explore whether eye movement behavior can be used as an objective tool to detect visual fatigue. Thirty-three participants were tested in this study. Their subjective visual fatigue survey, critical fusion frequency, and eye tracker of one minute gaze were measured before and after 20 minutes visual fatigue task. There were significant differences before and after visual fatigue task on survey and eye tracker-derived features. By multiple regression analysis with four eye tracker features, total fixation time duration of the inner circle, longest continuous duration of inner circle viewing time, maximum saccade distance, and focus radius, the regression R square value was greater than 0.9 for all critical fusion frequency data and when subjective visual fatigue assessment was greater than 12 points. In conclusion, eye movement behavior can be used to detect visual fatigue more sensitively even than the traditional critical flicker fusion assessment. Eye tracker can also provide well regression model to fit traditional critical fusion frequency measurement and subjective visual fatigue survey.
Highlights
As electronic products become more popular, people’s eyes were attracted on monitors for a long time, whether for work, study, or entertainment
Subjective visual fatigue assessment is usually performed through questionnaires based on selfreport information [1, 2], while objective visual fatigue assessment involves critical fusion frequency [3], and tools based on physiological signals, such as an EOG, are Journal of Sensors
The results of visual fatigue were obtained through questionnaires and critical fusion frequency (CFF)
Summary
As electronic products become more popular, people’s eyes were attracted on monitors for a long time, whether for work, study, or entertainment. This long-term use of the eye has already caused a decrease in vision. Many previous studies have shown that vision loss is related to long-term visual fatigue treatment, and visual fatigue hinders students’ learning, as well as the health of workplace workers, and even increase the frequency of road drivers’ car accidents. The visual fatigue study attracts great attention from academics and industry. Methods for estimating visual fatigue can be divided into two types: subjective and objective. Subjective visual fatigue assessment is usually performed through questionnaires based on selfreport information [1, 2], while objective visual fatigue assessment involves critical fusion frequency [3], and tools based on physiological signals, such as an EOG, are Journal of Sensors
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
