A novel frequency band selection method for Common Spatial Pattern in Motor Imagery based Brain Computer Interface

Gufei Sun, Jinglu Hu, Gengfeng Wu

研究成果: Conference contribution

22 被引用数 (Scopus)

抄録

Brain-Computer Interface (BCI) is a system provides an alternative communication and control channel between the human brain and computer. In Motor Imagery-based (MI) BCI system, Common Spatial Pattern (CSP) is frequently used for extracting discriminative patterns from the electroencephalogram (EEG). There are many studies have proven that the performance of CSP has a very important relation with the choice of operational frequency band. As the fact that the CSP features at different frequency bands contain discriminative and complementary information for classification, this paper proposes a new frequency band selection method to find the best frequency band set on which subject-specifics CSP are complementary for MI classification. Compared to the performance offered by the existing method based on frequency band partition, the proposed algorithm can yield error rate reductions of 49.70% for the same BCI competition dataset.

本文言語English
ホスト出版物のタイトル2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
DOI
出版ステータスPublished - 2010
イベント2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona, Spain
継続期間: 2010 7 182010 7 23

出版物シリーズ

名前Proceedings of the International Joint Conference on Neural Networks

Conference

Conference2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
CountrySpain
CityBarcelona
Period10/7/1810/7/23

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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