Chinese Journal of Tissue Engineering Research ›› 2010, Vol. 14 ›› Issue (43): 8061-8064.doi: 10.3969/j.issn.1673-8225.2010.43.021

Previous Articles     Next Articles

Feature extraction of electroencephalogram for imagery movement based on Mu/Beta rhythm

Huang Si-juan, Wu Xiao-ming　   

  1. School of Bioscience and Bioengineer, South China University of Technology, Guangzhou  510006, Guangdong Province, China　
  • Online:2010-10-22 Published:2010-10-22
  • Contact: Wu Xiao-ming, Doctoral supervisor, School of Bioscience and Bioengineer, South China University of Technology, Guangzhou 510006, Guangdong Province, China bmxmwus@scut.edu.cn
  • About author:Huang Si-juan★, Studying for master’s degree, School of Bioscience and Bioengineer, South China University of Technology, Guangzhou 510006, Guangdong Province, China huangsijuan123@163.com
  • Supported by:

     the Science and Technology Development Program of Guangdong Province, No. 2009B030801004*

PDF

1460

Abstract:

BACKGROUND: Different sports produce different electroencephalogram (EEG) signals. Brain-computer interface (BCI) utilized characteristics of EEG to communicate brain and external device by modern signal processing technique and external connections. The speed of EEG signals processing is important for BCI online research.
OBJECTIVE: To investigate a rapid and accurate method for extracting and classifying EEG for imagery movement.
METHODS: Using the attribute of event-related synchronization and event-related desynchronization during imagery movement, the BCI dataset of 2003 was processed. Mu/Beta rhythm was obtained from bandpass filtering and wavelet package analysis. Then feature was formed by the average energy of lead C3, C4, and was sorted out by the function classify of matlab.
RESULTS AND CONCLUSION: Appropriate parameters were obtained by detection of training data and used for identification of training data and testing data, with a correct rate of classification of 87.857% and 88.571%.

CLC Number: