期刊
IEEE TRANSACTIONS ON REHABILITATION ENGINEERING
卷 8, 期 2, 页码 203-205出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/86.847816
关键词
brain-computer interface (BCI); communication; control; electroencephalograph (EEG)-processing; machine learning; severe neuromuscular disability
A new parallel man-machine training approach to brain-computer interface (BCI) succeeded through a unique application of machine learning methods. The BCI system could train users to control an animated cursor on the computer screen by voluntary electroencephalogram (EEG) modulation. Our BCI system requires only two to four electrodes, and has a relatively short training time for both the user and the machine. Moving the cursor in one dimension, our subjects were able to hit 100% of randomly selected targets, while in two dimensions, accuracies of approximately 63% and 76% was achieved with our two subjects.
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