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
Link To Document :
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