Journal of Northeastern University ›› 2010, Vol. 31 ›› Issue (1): 12-15.DOI: -

• OriginalPaper • Previous Articles     Next Articles

Recognition based on common spatial patterns and ANN for brain-computer interface signal

Ye, Ning (1); Sun, Yu-Ge (1); Wang, Xu (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-20 Revised:2013-06-20 Online:2010-01-15 Published:2013-06-20
  • Contact: Ye, N.
  • About author:-
  • Supported by:
    -

Abstract: Classifies the EEG signals of different ideas based on the common spatial patterns(CSP) and LVQ-ANN. EEG is the control signals of brain-computer interface(BCI), which are collected from one's scalp by electrodes to extract and classify the EEG features so as to form a communication system that does not depend on the brain's normal output channels of peripheral nerves and muscles. With the original EEG signals preprocessed by wavelet packet decomposition, the CSP is introduced to decompose further the EEG signals from the specified subbands of wavelet packet so as to extract the best features and classify the features which are of different ideas by LVQ-ANN. Simulation result showed that the method proposed can provide a recognizable accuracy up to 92.7% in classification, it has come up to the standard for the practical application of BCI.

CLC Number: