EEG-based Brain-Computer Interface Using Subject-Specific Spatial Filters
Sensorimotor EEG rhythms are affected by motor imagery and can, therefore, be used as input signals for an EEG-based brain-computer interface (BCI). Satisfactory classification rates of imagery-related EEG patterns can be activated when multiple EEG recordings and the method of common spatial patterns is used for parameter estimation. Data from 3 BCI experiments with and without feedback are reported.