DocumentCode :
1005690
Title :
Continuous EEG classification during motor imagery-simulation of an asynchronous BCI
Author :
Townsend, George ; Graimann, Bernhard ; Pfurtscheller, Gert
Author_Institution :
Dept. of Comput. Sci., Algoma Univ., Sault Ste. Marie, Ont., Canada
Volume :
12
Issue :
2
fYear :
2004
fDate :
6/1/2004 12:00:00 AM
Firstpage :
258
Lastpage :
265
Abstract :
Nearly all electroencephalogram (EEG)-based brain-computer interface (BCI) systems operate in a cue-paced or synchronous mode. This means that the onset of mental activity (thought) is externally-paced and the EEG has to be analyzed in predefined time windows. In the near future, BCI systems that allow the user to intend a specific mental pattern whenever she/he wishes to produce such patterns will also become important. An asynchronous BCI is characterized by continuous analyzing and classification of EEG data. Therefore, it is important to maximize the hits (true positive rate) during an intended mental task and to minimize the false positive detections in the resting or idling state. EEG data recorded during right/left motor imagery is used to simulate an asynchronous BCI. To optimize the classification results, a refractory period and a dwell time are introduced.
Keywords :
electroencephalography; handicapped aids; medical signal processing; signal classification; asynchronous BCI; continuous EEG classification; dwell time; electroencephalogram-based brain-computer interface system; false positive detections; intended mental task; left motor imagery; mental activity; motor imagery; refractory period; right motor imagery; Biomedical engineering; Biomedical informatics; Brain modeling; Computer science; Detectors; Electroencephalography; Event detection; Feedback; Signal analysis; Synchronous motors; Adult; Algorithms; Brain Mapping; Communication Aids for Disabled; Computer Simulation; Data Display; Electroencephalography; Environment; Evoked Potentials, Motor; Humans; Imagination; Male; Motor Cortex; Online Systems; Pattern Recognition, Automated; User-Computer Interface;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2004.827220
Filename :
1304866
Link To Document :
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