title: Parallel man-machine training in development of EEG-based cursor control.
abstract: 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.
authors.affiliation: Faculty of Rehabilitation Medicine, The University of Alberta, Edmonton, Canada.
authors.forename: A
authors.initials: A
authors.lastname: Kostov
authors.forename: M
authors.initials: M
authors.lastname: Polak
mesh_terms: D001676:Biofeedback, Psychology / Q000502:physiology; D002540:Cerebral Cortex / Q000503:physiopathology*; D003143:Communication Devices for People with Disabilities; D004569:Electroencephalography / Q000295:instrumentation*; D005071:Evoked Potentials / Q000502:physiology; D006801:Humans; D016571:Neural Networks, Computer; D016262:Postpoliomyelitis Syndrome / Q000503:physiopathology / Q000534:rehabilitation; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D012984:Software; D014584:User-Computer Interface