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

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
George TownsendG Pfurtscheller

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.

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Jun 20, 2006·Annals of Biomedical Engineering·Ali BashashatiGary E Birch
Nov 23, 2006·Annals of Biomedical Engineering·S G MasonG E Birch
Jan 12, 2007·Journal of Computational Neuroscience·Mehrdad FatourechiRabab K Ward
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Feb 14, 2015·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Luis F Nicolas-AlonsoRoberto Hornero
Jun 27, 2013·IEEE Transactions on Bio-medical Engineering·Yuanqing LiZhuliang Yu
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