DocumentCode
747813
Title
How many people are able to operate an EEG-based brain-computer interface (BCI)?
Author
Guger, C. ; Edlinger, G. ; Harkam, W. ; Niedermayer, I. ; Pfurtscheller, G.
Author_Institution
Guger Technol. OEG, Graz, Austria
Volume
11
Issue
2
fYear
2003
fDate
6/1/2003 12:00:00 AM
Firstpage
145
Lastpage
147
Abstract
Ninety-nine healthy people participated in a brain-computer interface (BCI) field study conducted at an exposition held in Graz, Austria. Each subject spent 20-30 min on a two-session BCI investigation. The first session consisted of 40 trials conducted without feedback. Then, a subject-specific classifier was set up to provide the subject with feedback, and the second session - 40 trials in which the subject had to control a horizontal bar on a computer screen - was conducted. Subjects were instructed to imagine a right-hand movement or a foot movement after a cue stimulus depending on the direction of an arrow. Bipolar electrodes were mounted over the right-hand representation area and over the foot representation area. Classification results achieved with 1) an adaptive autoregressive model (39 subjects) and 2) band power estimation (60 subjects) are presented. Roughly 93% of the subjects were able to achieve classification accuracy above 60% after two sessions of training.
Keywords
biomechanics; biomedical electrodes; electroencephalography; feedback; handicapped aids; patient rehabilitation; user interfaces; 20 to 30 min; BCI; EEG-based brain-computer interface; adaptive autoregressive model; band power estimation; bipolar electrodes; cue stimulus; electroencephalogram; event-related desynchronization; feedback; foot movement; foot representation area; horizontal bar control; motor imagery; rehabilitation; right-hand movement; right-hand representation area; subject specific classifier; Brain computer interfaces; Brain modeling; Communication channels; Electrodes; Electroencephalography; Feedback; Foot; Head; Humans; Laboratories; Adaptation, Physiological; Adult; Brain; Electroencephalography; Evoked Potentials; Evoked Potentials, Visual; Feedback; Humans; Photic Stimulation; Psychomotor Performance; Reproducibility of Results; Sensitivity and Specificity; Task Performance and Analysis; Thinking; User-Computer Interface; Visual Perception;
fLanguage
English
Journal_Title
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1534-4320
Type
jour
DOI
10.1109/TNSRE.2003.814481
Filename
1214705
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