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Flight missions and remotely piloted aircraft operations can be taxing on pilots and operators and sustained workload may lead to performance decrements. One possibility to prevent this decline is to monitor cognitive workload to provide information that can be used to proactively enable real-time assistance to pilots and/or operators before performance is degraded. Heart rate and eye measures are two psychophysiological measurements that have been demonstrated as sensitive indicators of an operator's functional state, specifically cognitive workload, during tasks of varying levels of difficulty. These metrics are typically studied separately, but may be more robust indicators if integrated. The current study examined the relationship between heart rate and eye movements in response to varying levels of task difficulty and automation reliability to determine if integrating these metrics added any value to discerning workload. The study simultaneously collected electrocardiogram (ECG) and eye-tracking data from ten participants as they performed an aviation simulation task. Difficulty levels of three subtasks were manipulated in addition to the automation reliability of a fourth subtask. Performance data were analyzed for changes based on task difficulty and automation reliability; performance changes were statistically significant as workload increased and automation reliability varied. Heart rate and specific eye measures (e.g., fixation duration, pupil size, and blink rate) will be analyzed for changes reflecting the workload and automation.

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Honors Thesis

Primary Advisor

Thomas F. Eggemeier

Primary Advisor's Department



Stander Symposium poster

Integrating Heart Rate and Eye Movement Measures as a Possible Robust Indicator of Workload in an Aviation Simulation Task