Title
Online Control of a Brain-Computer Interface Using Phase Synchronization
Abstract
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.
Year
DOI
Venue
2006
10.1109/TBME.2006.881775
Biomedical Engineering, IEEE Transactions
Keywords
Field
DocType
biomedical electrodes,electroencephalography,handicapped aids,medical signal processing,synchronisation,EEG,bandpower,electrodes,electroencephalogram,electroencephalographic signals,feature vectors,mental states,motor imagery,online brain-computer interface control,phase locking value,phase synchronization,univariate adaptive autoregressive parameters,Brain-computer interface,electroencephalogram,motor imagery,phase locking,synchronization
Computer vision,Autoregressive model,Feature vector,Synchronization,Feature selection,Computer science,Brain–computer interface,Phase synchronization,Speech recognition,Artificial intelligence,Electroencephalography,Motor imagery
Journal
Volume
Issue
ISSN
53
12
0018-9294
Citations 
PageRank 
References 
31
2.32
1
Authors
4
Name
Order
Citations
PageRank
Brunner, C.1312.32
Scherer, R.2312.32
Graimann, B.3312.32
Supp, G.4312.32