A New Discriminative Common Spatial Pattern Method for Motor Imagery Brain-Computer Interfaces

• Published in: IEEE transactions on biomedical engineering Vol. 56; no. 11; pp. 2730 - 2733
• Main Authors: Thomas, Kavitha P., Guan, Cuntai, Lau, Chiew Tong, Vinod, A. P., Ang, Kai Keng
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2009; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Band pass filters; Brain Mapping - methods; Brain-computer interface; Councils; Discriminant Analysis; electroencephalogram; Electroencephalography; Electroencephalography - methods; Error analysis; Evoked Potentials, Motor - physiology; Feature extraction; Filter bank; Frequency synchronization; Humans; Imagination - physiology; Motor Cortex - physiology; Motor drives; motor imagery; Pattern Recognition, Automated - methods; Reproducibility of Results; Sensitivity and Specificity; Support vector machine classification; Support vector machines; User-Computer Interface
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2009.2026181

Event-related desynchronization/synchronization patterns during right/left motor imagery (MI) are effective features for an electroencephalogram-based brain-computer interface (BCI). As MI tasks are subject-specific, selection of subject-specific discriminative frequency components play a vital role in distinguishing these patterns. This paper proposes a new discriminative filter bank (FB) common spatial pattern algorithm to extract subject-specific FB for MI classification. The proposed method enhances the classification accuracy in BCI competition III dataset IVa and competition IV dataset IIb. Compared to the performance offered by the existing FB-based method, the proposed algorithm offers error rate reductions of 17.42% and 8.9% for BCI competition datasets III and IV, respectively.