Authors:
Lucille Lecoutre
1
;
Sami Lini
1
;
Christophe Bey
2
;
Quentin Lebour
1
and
Pierre-Alexandre Favier
2
Affiliations:
1
Akiani, France
;
2
CNRS IMS UMR 5218, France
Keyword(s):
EEG, Mental Workload, Operational Situation, Video Games.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Biofeedback Technologies
;
Biosignal Acquisition, Analysis and Processing
;
Human-Computer Interaction
;
Methodologies and Methods
;
Observation, Modeling and Prediction of User Behavior
;
Pattern Recognition
;
Physiological Computing Systems
;
Software Engineering
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 workl
oad 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.
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