A Brain Computer Interface Based on Wavelet Packet and Support Vector Machine with a Voting Mechanism

摘要：

　　In this paper, a novel method was proposed based on wavelet packet decomposition (WPD) for extracting the brainwave features from EEG signals, and support vector machines (SVMs) for mental task classification.Besides, an original voting mechanism was put forward for the final decision of classification.Moreover, some useful preprocessing methods were also applied.Segmentation along the time axis for fast response and increasing the correct classification rate, nonlinear and linear normalization for emphasizing the important information in small magnitude and optimizing data distribution.Furthermore, an especial grouping method was put forward to realize optimizing several parameters automatically.The simulation results have proved the effectiveness of the proposed method.

关键词： brain computer interface (BCI) wavelet packet decomposition (WPD) support vector machines (SVMs) voting mechanism grouping method

作者: Guang YANG Kenji NAKAYAMA Akihiro HIRANO

作者单位: Graduate School of Natural Science and Technology, Kanazawa University, Kakuma-machi,Kanazawa, Ishikawa 920-1192, Japan

会议类型: 国内会议

会议名称: Thirteenth Chinese Conference,SSTA 2011(第十三届中国系统仿真技术及其应用学术会议)

会议地点: 黄山

会议语种:英文

页码: 408-413

在线出版日期: 2011-08-03（万方平台首次上网日期，不代表论文的发表时间）