Application of neural network to brain-computer interface

Wei Yen Hsu, I. Jen Chiang

研究成果: 書貢獻/報告類型會議貢獻

3 引文 斯高帕斯(Scopus)

摘要

In this study, an neural-network-based system is proposed for the applications of brain-computer interface (BCI). Applying event-related brain potential (ERP) data acquired from the sensorimotor cortices, the system consists of three procedures, including enhanced active segment selection, feature extraction, and classification. Firstly, combined with the use of continuous wavelet transform (CWT) and Student's two-sample t-statistics, the 2D anisotropic Gaussian filter is proposed to further refine the active-segment selection. Multiresolution fractal features are then extracted from wavelet data by means of modified fractal dimension. Finally, support vector machine (SVM) is used for classification. Compared with other approaches on motor imagery data, the results indicate that the proposed method is promising in BCI applications.

原文英語
主出版物標題Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012
頁面163-168
頁數6
DOIs
出版狀態已發佈 - 2012
事件2012 IEEE International Conference on Granular Computing, GrC 2012 - HangZhou, 中国
持續時間: 八月 11 2012八月 13 2012

其他

其他2012 IEEE International Conference on Granular Computing, GrC 2012
國家/地區中国
城市HangZhou
期間8/11/128/13/12

ASJC Scopus subject areas

  • 軟體

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