title: Detection of movement-related desynchronization patterns in ongoing single-channel electrocorticogram.
abstract: Adaptive autoregressive parameters and a linear classifier were used to detect movement related desynchronization and synchronization patterns in single-channel electrocorticogram (ECoG) obtained from implanted electrode grids. The best classification accuracies found had more than 90% hits and less than 10% false positives. The findings show that the detection of event-related desynchronization and synchronization in ECoG data can be used to reliably provide switch control directly by the brain and is therefore very suitable as the basis of a direct brain interface.
mesh_terms: D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D002540:Cerebral Cortex / Q000503:physiopathology*; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000145:classification / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis / Q000503:physiopathology*; D005071:Evoked Potentials; D005189:False Positive Reactions; D006801:Humans; D009068:Movement; D010363:Pattern Recognition, Automated; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013223:Statistics as Topic; D013647:Task Performance and Analysis