Title :
Toward a direct brain interface based on human subdural recordings and wavelet-packet analysis
Author :
Graimann, Bernhard ; Huggins, Jane E. ; Levine, Simon P. ; Pfurtscheller, Gert
Author_Institution :
Inst. of Human Comput. Interfaces, Graz Univ. of Technol., Austria
fDate :
6/1/2004 12:00:00 AM
Abstract :
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.
Keywords :
biomechanics; electroencephalography; genetic algorithms; handicapped aids; medical computing; neurophysiology; direct brain interface; electrocorticogram channels; event-related desynchronization; event-related potentials; event-related synchronization; genetic algorithm; human subdural recordings; motor tasks; movement related patterns; wavelet-packet analysis; Biomedical engineering; Brain; Communication system control; Computer interfaces; Electrodes; Electroencephalography; Enterprise resource planning; Humans; Switches; Wavelet packets; Action Potentials; Algorithms; Cerebral Cortex; Electrodes, Implanted; Electroencephalography; Epilepsy; Evoked Potentials, Motor; Humans; Movement; Neurons; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; User-Computer Interface;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2004.826671