TY - GEN
T1 - BMFLC with neural network and de for better event classification
AU - Wang, Yubo
AU - Gonuguntla, Venkateswarlu
AU - Shafiq, Ghufran
AU - Veluvolu, Kalyana C.
PY - 2013
Y1 - 2013
N2 - The event-related desynchronization(ERD) is a well known phenomenon that is commonly used for classification in brain-computer interface(BCI) applications. The classification accuracy of ERD based BCI can be improved by selection of subject-specific reactive band rather than complete μ-band. After obtaining time-frequency(TF) mapping of EEG signal with a Fourier based adaptive method, differential evolution(DE) is used for the identification of the reactive band. Compared to classical band-power based method, the proposed method based on subject-specific reactive band yields better accuracy with BCI competition dataset IV.
AB - The event-related desynchronization(ERD) is a well known phenomenon that is commonly used for classification in brain-computer interface(BCI) applications. The classification accuracy of ERD based BCI can be improved by selection of subject-specific reactive band rather than complete μ-band. After obtaining time-frequency(TF) mapping of EEG signal with a Fourier based adaptive method, differential evolution(DE) is used for the identification of the reactive band. Compared to classical band-power based method, the proposed method based on subject-specific reactive band yields better accuracy with BCI competition dataset IV.
KW - Classification
KW - motor imagery
KW - Optimal Band
UR - https://www.scopus.com/pages/publications/84877720112
U2 - 10.1109/IWW-BCI.2013.6506621
DO - 10.1109/IWW-BCI.2013.6506621
M3 - Conference contribution
AN - SCOPUS:84877720112
SN - 9781467359733
T3 - 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013
SP - 34
EP - 35
BT - 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013
T2 - 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013
Y2 - 18 February 2013 through 20 February 2013
ER -