ABSTRACT
The present study examined the sensitivity of several candidate metrics of real-time workload within the spatial component of an unmanned aerial vehicle (UA V) task. Advanced Brain Monitoring ' s (i\BM) wireless B -Alert system was used to collect participant ' s EEG workload and engagement data. Eye tracking data was also collected. The UA V simulation required participants to report heading information of moving vehicles, as seen from the UA V. There were four blocks of difficulty, over which a significant performance decrement was shown. Additionally, participants rated their workload significantly higher and pupil diameter significantly increased across blocks of increasing difficulty, as well as within each block during periods of highest mental demand. ABM's workload and engagement
metrics howevcr did not show a significant change over or within blocks . The results showed that pupil diameter shows promise as a correlate of mental workload.
