Embedded Brain Reading in a Complex Virtual Environment
Hendrik Wöhrle, Johannes Teiwes, Marc Tabie, Elsa Andrea Kirchner
series DFKI Documents, volume 14-07, pages 2, Nov/2014. DFKI GmbH, Universität Bremen.
High mental workload can overwhelm a human operator. This can in certain setups (e.g. pilots, robot control)
result in potentially dangerous situations. Overly complex and unintelligent human machine interfaces (HMIs)
can have a negative effect, e.g., loss of situation awareness, in critical situations. Here, we propose the usage
of adaptive online single-trial analysis of the electroencephalogram (EEG) to estimate the task engagement
of the operator and adjust the HMI of a virtual robot control environment accordingly. By doing this, we
will investigate if the amount of errors that are caused by an excessive demand of the human operator can
be decreased or the effectiveness can be improved by reducing the amount of time that is required to finish
a mission in the scenario.