title: Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters.
abstract: Electroencephalogram (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by, e.g., patients with amyotrophic lateral sclerosis (ALS) to develop a simple binary response in order to reply to specific questions. Four subjects participated in a series of on-line sessions with an EEG-based cursor control. The EEG was recorded from electrodes overlying sensory-motor areas during left and right motor imagery. The EEG signals were analyzed in subject-specific frequency bands and classified on-line by a neural network. The network output was used as a feedback signal. The on-line error (100%-perfect classification) was between 10.0 and 38.1%. In addition, the single-trial data were also analyzed off-line by using an adaptive autoregressive (AAR) model of order 6. With a linear discriminant analysis the estimated parameters for left and right motor imagery were separated. The error rate obtained varied between 5.8 and 32.8% and was, on average, better than the on-line results. By using the AAR-model for on-line classification an improvement in the error rate can be expected, however, with a classification delay around 1 s.
authors.affiliation: Ludwig-Boltzmann Institute for Medical Informatics and Neuroinformatics and Department of Medical Informatics, Institute for Biomedical Engineering, Graz University of Technology, Austria.
authors.forename: G
authors.initials: G
authors.lastname: Pfurtscheller
authors.forename: C
authors.initials: C
authors.lastname: Neuper
authors.forename: A
authors.initials: A
authors.lastname: Schlögl
authors.forename: K
authors.initials: K
authors.lastname: Lugger
mesh_terms: D000328:Adult; D002540:Cerebral Cortex / Q000502:physiology*; D003344:Cortical Synchronization; D003463:Cues; D016002:Discriminant Analysis; D004569:Electroencephalography; D004576:Electromyography; D005246:Feedback / Q000502:physiology; D005260:Female; D006801:Humans; D007092:Imagination / Q000502:physiology*; D008297:Male; D009068:Movement / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted