Document Type

Conference Paper


Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence


Computer Sciences

Publication Details

International Symposium on Human Mental Workload: Models and Applications


The capacity to assess and manage mental workload is becoming more and more relevant in the current work environments as it helps to prevent work related accidents and achieve better efficiency and productivity. Mental workload is often measured indirectly by inferring its effects on performance, mental states, and psychophysiological indexes. Since these three main axes should reflect changes in task demands, convergence between measures is expected, however research has found that this convergence is not to be taken for granted as it is not often present. This study aims to explore how the task demand transition peak point may affect in mental workload divergence between measures during taskload changes: some measures might be more sensitive to abrupt changes in task demand than others and this could also be mediated by the task-load baseline. This was tested by manipulating task-load transitions and the point at which the change in the task load magnitude reaches its highest relative peak over time during a monitoring experiment, while psychophysiological (pupil size) and subjective perceptions were collected as indicators of subjects’ workload alongside objective indicators of task performance from the simulation. The results showed that performance measure proved to be sensitive to abrupt increases in task demand in every condition whereas our physiological measure was only sensitive to a sudden increase in task-load during low mental workload baseline circumstances. Furthermore, contrary to what expected, subjective ratings of mental workload did not react to abrupt transitions in task-load in every condition but only to an absolute measure of the overall level of task demand.