Work, aging, mental fatigue, and eye movement dynamics

Mental load and fatigue are important multidimensional phenomena concerning aging and computer work. Fatigue may be associated with reduced cognitive resources and increased errors. Micro-breaks are strategic solutions to impede fatigue subject to design constraints, such as a timing plan. The present work aimed to use eye tracking as a promising technology to measure mental load and fatigue in young and elderly adults (Studies I and II), and to apply micro-breaks based on fatigue-related changes in eye movements to decelerate fatigue development (Study III).
A novel task resembling computer work was developed to induce mental load in young and elderly individuals (Study I). Eye movements were recorded during the task execution. The task was performed with three load levels across two days. In addition to the load effects on performance, perceived workload, and the oculometrics, the test-retest reliability of 19 oculometrics was assessed. In Study II, the effect of 40-min time-on-task was explored on oculometrics. Then, a predictive model of fatigue was developed (Study III). Oculometrics-based biofeedback was implemented to detect fatigue using the developed model, which triggered micro-breaks upon fatigue detection to impede it. Perceived fatigue and workload were compared between a session with the biofeedback and a control session with self-triggering micro-breaks.
A set of oculometrics were found to reflect mental load (Study I) and fatigue (Study II) in both age groups. Similar trends in oculometrics with increased mental load and fatigue, implying shared neural systems for both conditions (Studies I and II). Age-related differences were exhibited in a few of the oculometrics (Study II), but age as a feature did not significantly contribute to fatigue detection (Study III). The biofeedback reduced workload and fatigue development, suggesting an improved strategy to design the timing plan of micro-breaks (Study III). Overall, the findings may support the viability of detecting the effects of fatigue and mental load on oculometrics to apply oculometrics-based biofeedback in computer work.