THE RELATIONSHIP OF PERCEIVED WORKLOAD AND PSYCHOMOTOR PERFORMANCE TO BRAIN DYNAMICS DURING VARYING DEGREES OF TASK DEMAND AND CONTROLLABILITY IN A FLIGHT-RELATED COMPENSATORY TRACKING TASK
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The assessment and prediction of cognitive-motor performance holds great importance for any discipline connected to human operators in the context of safety-critical behavior. A study of mental workload is essential to understanding the intrinsic limitations of the human information processing system, and the resultant cognitive-motor behavior. Mental workload and the quality of cognitive-motor performance are generally known to be impacted by task demand. However, one feature of task demand far less understood is the controllability of a system (e.g. the responsiveness of a flight platform and its handling qualities). In the realm of Human-Machine Interface, the assessment of system controllability has typically been conducted through subjective measurements, such as the Cooper-Harper Rating Scale, a widely used metric in aircraft design to measure perceived operator workload and handling qualities, first proposed in 1969. A fundamental element of the decision making process for handling qualities associated with operator workload includes the reporting of the control compensation required to overcome deficiencies and errors that could impact and inhibit the successful completion of a task. Yet, the Cooper-Harper Rating Scale, and all other subjective rating scales are limited by a lack of objectivity, reliability, reduced sensitivity to dynamic changes in operator workload, and, are solely dependent on subjective estimates of effort to control compensation within a system, despite such wide usage in the field. To overcome such limitations, the contribution of this dissertation is the estimation of perceived operator workload, based on objective brain dynamics captured during varying levels of task demand and controllability. Therefore, the objective of this dissertation was to ascertain how objective brain dynamics and subjective ratings would respond to flight-related compensatory tracking tasks when handling qualities and task demand are manipulated. More specifically, this dissertation assessed the relationship between objective brain dynamics and subjective rating scales explicitly related to mental workload, as reported during compensatory tracking tasks of varying complexity, while also challenged with progressively increasing levels of controllability (i.e., levels of handling qualities). Thus, Aim 1 was to assess the effects of varying levels of handling qualities (i.e., HQR1, HQR2, HQR3) on mental workload and psychomotor performance. Aim 2 was to investigate the effects of increased task demand (i.e., Single-axis vs. Multi-axis) on mental workload and psychomotor performance. Finally, Aim 3 was to examine the empirical relationship between objective brain dynamics and subjective ratings of workload. Accordingly, this dissertation employed a 2 Condition (Single-axis vs. Multi-axis) x 3 Level of Handling Qualities (HQR1, HQR2, HQR3) design. Perceived workload, psychomotor performance, and brain dynamics, derived from EEG power spectra and spectro-temporal analyses, were assessed in twenty-two volunteer participants in the Naval Reserve Officers’ Training Corps. Overall, the findings of this dissertation support a characterization of the human information processing system as a finite resource with a limited capacity. When challenged with increasing levels of handling qualities, parietal alpha power decreased, behavioral performance was significantly attenuated, and subjective ratings of workload were higher, as was expected. Accordingly, there was a significant relationship between objective brain dynamics and subjective ratings of workload. Furthermore, an exploratory wavelet-based analysis revealed some generally high cross-correlations between brain dynamics and psychomotor performance, which may inform future research efforts of more dynamic measurement strategies to capture perceived workload with increased fidelity. Therefore, the results of this dissertation underscore the usage of objective brain dynamics to supplement subjective rating scales, which can provide additional insights to enhance our understanding of brain and motor coordination under varying levels of task demand and system handling qualities.