Design of a Decision-Making Task for a Collaborative Brain-Computer Interface System Based on Emotiv EEG

摘要

This article presents lessons learned in the design, implementation and evaluation of a task of computerized decision-making to be used in a non-invasive collaborative and hybrid brain-computer interface, which used the Emotiv EEG for extract neural feature and response time as behavioral feature. The task developed was based on RSVP and has controlled levels of difficulty that can cause uncertainty. It is believed that the participants' general satisfaction was good, since the majority indicated that they had an easy understanding of the task. The task proved to be efficient for the initial purpose, that is, to generate difficulty to the participants and the experiment can be balanced with respect to the difficulty of executing the task. However, it was not possible to find relationships between the emotions felt by the participants in their subjective answers and in their emotions collected through the Emotiv EEG. It was possible to verify that the participants with less response time tend to answer more correctly, which can indicate their level of confidence, as expected.