Physiological Predictors of Operator Performance: The Role of Mental Effort and Its Link to Task Performance.

Abstract

Objective: The present study investigated how pupil size and heart rate variability (HRV) can contribute to the prediction of operator performance. We illustrate how focusing on mental effort as the conceptual link between physiological measures and task performance can align relevant empirical findings across research domains.

Background: Physiological measures are often treated as indicators of operators' mental state. Thereby, they could enable a continuous and unobtrusive assessment of operators' current ability to perform the task.

Method: Fifty participants performed a process monitoring task consisting of ten 9-minute task blocks. Blocks alternated between low and high task demands, and the last two blocks introduced a task reward manipulation. We measured response times as primary performance indicator, pupil size and HRV as physiological measures, and mental fatigue, task engagement, and perceived effort as subjective ratings.

Results: Both increased pupil size and increased HRV significantly predicted better task performance. However, the underlying associations between physiological measures and performance were influenced by task demands and time on task. Pupil size, but not HRV, results were consistent with subjective ratings.

Conclusion: The empirical findings suggest that, by capturing variance in operators' mental effort, physiological measures, specifically pupil size, can contribute to the prediction of task performance. Their predictive value is limited by confounding effects that alter the amount of effort required to achieve a given level of performance.

Application: The outlined conceptual approach and empirical results can guide study designs and performance prediction models that examine physiological measures as the basis for dynamic operator assistance.