Continuous detection of motor imagery in a four-class asynchronous BCI.

Full Abstract

Asynchronous Brain Computer Interface (BCI) is an important class of BCI systems that has not received enough attention from the BCI community. In this work we introduce for the first time a system for classification of four different motor imageries in the context of an asynchronous BCI system which distinguishes between periods of movement imagination occurrence and idling or resting periods of ongoing EEG signal as well as classifying the 4 class motor imageries. We used two multi class extensions of the method of Common Spatial Patterns (CSP) for feature extraction and LDA, SVM, and MDA well known classifiers for combination purposes. We have applied our procedure to data set IIIa from BCI Competition III [2]. Offline evaluation of a prototype system demonstrated true positive rates in the range of 56%-88% with corresponding false positive rates in the range of 18%-9%.

Author information

Author/s: Sadeghian, E B (EB); Moradi, M H (MH);

Affiliation: Biomedical Engineering Department, Amir Kabir University of Technology (Tehran Polytechnic), Tehran, Iran. e_bsadeghian(-atsign-)aut.ac.ir

Journal and publication information

Publication Type: Comparative Study; Evaluation Studies; Journal Article; Validation Studies

Journal: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference (Conf Proc IEEE Eng Med Biol Soc), published in United States. (Language: eng)

Reference: 2007-; vol 2007 (issue ) : pp 3241-4

Dates: Created 2007/11/16; Completed 2008/03/27;

PMID: 18002686, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: 18 Feb 2009 00:00:00)

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