DocumentCode :
2223046
Title :
Subclass discriminant analysis using dynamic cluster formation for EEG-based brain-computer interface
Author :
Oveisi, Farid
Author_Institution :
MSR Res. Inst., Tehran, Iran
fYear :
2009
fDate :
April 29 2009-May 2 2009
Firstpage :
303
Lastpage :
306
Abstract :
An important issue in pattern recognition is to extract features that have more discriminant power. In this context, one of the most effective approaches for optimal feature extraction is subclass discriminant analysis. However, in this approach, the major problem is to determine the optimal number of subclasses in each class. This paper presents a novel approach for efficient feature extraction via subclass discriminant analysis using dynamic cluster formation (DSDA). The main component of this paper is to design a method to automatically discover the optimal set of subclasses in each class. The effectiveness of the proposed method is evaluated by using the classification of EEG signals. The tasks to be discriminated are the imaginative hand movement and the resting state. The results demonstrate that the proposed method performed well in several experiments on different subjects and can improve the classification accuracy in the BCI systems.
Keywords :
brain-computer interfaces; electroencephalography; feature extraction; medical signal processing; pattern clustering; signal classification; BCI system; EEG-based brain-computer interface; dynamic cluster formation; feature extraction; signal classification; subclass discriminant analysis; Brain computer interfaces; Covariance matrix; Feature extraction; Independent component analysis; Linear discriminant analysis; Neural engineering; Principal component analysis; Scattering; Signal processing; Signal processing algorithms; brain computer interface; dynamic cluster formation; feature extraction; subclass discriminant analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on
Conference_Location :
Antalya
Print_ISBN :
978-1-4244-2072-8
Electronic_ISBN :
978-1-4244-2073-5
Type :
conf
DOI :
10.1109/NER.2009.5109293
Filename :
5109293
Link To Document :
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