Online control of a brain-computer interface using phase synchronization

Clemens Brunner, Reinhold Scherer, Bernhard Graimann, Gernot Supp, Gert Pfurtscheller

Research output: Contribution to journalArticlepeer-review


Currently, almost all brain-computer interfaces (BCIs) ignore the relationship between phases of electroencephalographic signals detected from different recording sites (i.e., electrodes). The vast majority of BCI systems rely on feature vectors derived from e.g., bandpower or univariate adaptive autoregressive (AAR) parameters. However, ample evidence suggests that additional information is obtained by quantifying the relationship between signals of single electrodes, which might provide innovative features for future BCI systems. This paper investigates one method to extract the degree of phase synchronization between two electroencephalogram (EEG) signals by calculating the so-called phase locking value (PLV). In our offline study, several PLV-based features were acquired and the optimal feature set was selected for each subject individually by a feature selection algorithm. The online sessions with three trained subjects revealed that all subjects were able to control three mental states (motor imagery of left hand, right hand, and foot, respectively) with single-trial accuracies between 60% and 66.7% (33% would be expected by chance) throughout the whole session
Original languageEnglish
Pages (from-to)2501-2506
JournalIEEE Transactions on Biomedical Engineering
Issue number12
Publication statusPublished - 2006


Dive into the research topics of 'Online control of a brain-computer interface using phase synchronization'. Together they form a unique fingerprint.

Cite this