Continuous EEG classification during motor imagery--simulation of an asynchronous BCI.

Full 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.

Author information

Author/s: Townsend, George (G); Graimann, Bernhard (B); Pfurtscheller, Gert (G);

Affiliation: Department of Computer Science, Algoma University, Sault Ste. Marie, ON P6A 2G4, Canada. townsend(-atsign-)auc.ca

Journal and publication information

Publication Type: Clinical Trial; Journal Article

Journal: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society (IEEE Trans Neural Syst Rehabil Eng), published in United States. (Language: eng)

Reference: 2004-Jun; vol 12 (issue 2) : pp 258-65

Dates: Created 2004/06/28; Completed 2004/12/21;

PMID: 15218939, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: )

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