Toward a direct brain interface based on human subdural recordings and wavelet-packet analysis.
Highly accurate asynchronous detection of movement related patterns in individual electrocorticogram channels has been shown using detection based on either event-related potentials (ERPs) or event-related desynchronization and synchronization (ERD/ERS). A method using wavelet-packet features selected with a genetic algorithm was proposed to simultaneously detect ERP and ERD/ERS and was tested on data from seven subjects and four motor tasks. The proposed wavelet method performed better than previous methods with perfect detection for four subject/task combinations and hit percentages greater than 90% with false positive percentages less than 15% for at least one task for all seven subjects.
Graimann
Bernhard
B
Institute of Human Computer Interfaces, University of Technology Graz, A-8010 Graz, Austria. graimann@tugraz.at
Huggins
Jane E
JE
Levine
Simon P
SP
Pfurtscheller
Gert
G
D000200:Action Potentials; D000465:Algorithms; D002540:Cerebral Cortex / Q000503:physiopathology*; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000503:physiopathology*; D019054:Evoked Potentials, Motor; D006801:Humans; D009068:Movement; D009474:Neurons; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface