Evaluating EEG measures as a workload assessment in an operational video game setup

Abstract

We tested the electroencephalography (EEG) B-Alert X10 system (Advance Brain Monitoring, Inc.) mental workload metrics. When we evaluate a human-systems interfaces (HSI), we need to assess the operator's state during a task in order evaluate the systems efficiency at helping the operator. Physiological metrics are of good help when it comes to evaluate the operator's mental workload, and EEG is a promising tool. The B-Alert system includes an internal signal processing algorithm computing a mental workload index. We set up a simple experiment on a video game in order to evaluate the reliability of this index. Participants were asked to play a video game with different levels of goal (easy vs hard) as we measured subjective, behavioral and physiological indices (B-Alert mental workload index, pupillometry) of mental workload. Our results indicate that, although most of the measure point toward the same direction, the B-Alert metrics fails to give a clear indication of the mental workload state of the participants. The use of the B-Alert workload index alone is not precise enough to assess an operator mental workload condition with certainty. Further evaluations of this measure need to be done.