Department of Human and Systems EngineeringWith the advancement of display technologies, more diverse display products are available around us. VDT (Visual Display Terminal) tasks are, however, associated with various visual fatigue symptoms that can reduce work efficiency and task performance. Such results can be more severe for older individuals with diminished visual abilities, which typically start around the age of 40. However, studies on visual fatigue of older individuals are relatively fewer than those for younger individuals. Though, proper work-rest schedules are deemed to reduce visual fatigue, workers have difficulty in taking rest breaks due to many reasons. It is expected that a real-time rest reminder will be effective because the time to onset of visual fatigue can vary as visual fatigue is affected by many factors including individual and task characteristics. Curved displays provide relatively even viewing distances across their display surface for the center viewer than flat displays, which could benefit viewing experience while reducing visual fatigue. Indeed, some studies on display curvature demonstrated that curved displays are more effective than flat displays in terms of task performance, visual fatigue, and preference. Previously, various physiological measures (e.g. accommodation amplitude and near point accommodation) were considered as indices of visual fatigue. Using these measures to predict visual fatigue in daily life are, however, not practical because of difficulties in measuring and/or needs for high-cost equipment.
The aims of the current study were 1) to examine the effects of task duration, display curvature, and presbyopia on physiological and perceived visual fatigue and display satisfaction associated with performing proofreading tasks on 27??? displays, and 2) to develop a prediction model for visual fatigue using pupil- and bulbar conjunctiva-related measurements which can be easily obtained in daily life.
A total of 64 participants (32 for each age group) performed a 1-hr proofreading task. The current study considered task duration (within-subjects0, 15, 30, 45, and 60 min), display curvature (between-subjects600mm, 1140mm, 4000mm, and flat) and age group [between-subjectsyounger (20-35 yrs) and older (45-60 yrs)] as independent variables. Pupil diameter, bulbar conjunctival redness, perceived visual fatigue [measured in ECQ (Eye Complaint Questionnaire) scores], and display satisfaction were obtained every 15 minutes, while CFF (Critical Fusion Frequency) was obtained pre and post the 1-hr proofreading task.
The rear-projection environment was comprised of 27??? curved rear screens, a beam projector, and the Warpalizer software. Environmental factors that can affect visual fatigue were controlled. An eye tracking system, a digital camera, and a flicker fusion system were used to measure physiological measures of visual fatigue, and a series of questionnaires were used to measure perceived visual fatigue and satisfaction of display. 3-way ANOVA was used to examine how 3 independent variables and their interactions affected each of 5 dependent variables. Four methods were considered in developing prediction models for visual fatigue and display satisfaction, and the developed models were compared in terms of predictive accuracy.
The results showed that over the 1-hr task, pupil diameters decreased (5.1%), bulbar conjunctival redness increased (18.8%), CFF thresholds decreased (0.94%), and ECQ scores increased (207%), all indicating an increase in visual fatigue. Even with a 15 min of VDT task, visual fatigue increased significantly. At the 1140mm curvature, pupil diameters were the largest, indicating less visual fatigue, and the display satisfaction of the older group, though not significant, gradually increased over the 1-hr task, indicating a less increase in visual fatigue. Display satisfaction was not affected by any independent variables. In terms of predictive accuracy of visual fatigue, the artificial neural network model was the best followed by the 3rd degree polynomial regression model.
The results of this study can be utilized when scheduling work-rest, determining a better display curvature for 27??? displays, and predicting visual fatigue in real time to notify the time to take a rest.ope
