2011/06/10 by Pavel Bobrov, Alexander Frolov, Charles R. Cantor +3 · 1 voice
Neuroscience · #EEG and Brain-Computer Interfaces #Neural and Behavioral Psychology Studies #Neural dynamics and brain function
paper · pdf · doi:10.1371/journal.pone.0020674
openalex publication_date 2011/06/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
This paper examines the task of recognizing EEG patterns that correspond to performing three mental tasks: relaxation and imagining of two types of pictures: faces and houses. The experiments were performed using two EEG headsets: BrainProducts ActiCap and Emotiv EPOC. The Emotiv headset becomes widely used in consumer BCI application allowing for conducting large-scale EEG experiments in the future. Since classification accuracy significantly exceeded the level of random classification during the first three days of the experiment with EPOC headset, a control experiment was performed on the fourth day using ActiCap. The control experiment has shown that utilization of high-quality research equipment can enhance classification accuracy (up to 68% in some subjects) and that the accuracy is independent of the presence of EEG artifacts related to blinking and eye movement. This study also shows that computationally-inexpensive bayesian classifier based on covariance matrix analysis yields similar classification accuracy in this problem as a more sophisticated Multi-class Common Spatial Patterns (MCSP) classifier.