A new discriminative common spatial pattern method for motor imagery brain-computer interfaces.
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.
Thomas
Kavitha P
KP
School of Computer Engineering, Nanyang Technological University, Singapore, Singapore. kavi0003@ntu.edu.sg
Guan
Cuntai
C
Lau
Chiew Tong
CT
Vinod
A P
AP
Ang
Kai Keng
KK
D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D016002:Discriminant Analysis; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology*; D006801:Humans; D007092:Imagination / Q000502:physiology*; D009044:Motor Cortex / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface