An Automatic Optimum Data Selection Method For EEG-based Brain-computer Interface

摘要：

An electroencephalogram (EEG) based Brain-Computer Interface (BCI) is aimed at developing a system that can support communication possibilities for patients with severe neuromuscular disabilities through EEG pattern recognition and classification. Previously many parametric modeling techniques for EEG analysis have been developed and improved upon. For this work we analyzed five parameters on seven subjects to study their influence on brain computer interface (BCI) classification. Our study shows that these parameters greatly influence classification accuracy with subject dependent parameters. This suggests that the parameter selection process should be analyzed further when building models.

作者: Peng Zhou Hongbao Cao Jiayi Ge Xin Zhao Mingshi Wang

作者单位: College of Precision Instrument & Opto-electronic Engineering, Tianjin University, Tianjin 300072, C Department of Biomedical Egnineering, Louisiana Tech University, Ruston, LA, USA

会议类型: 国际会议

会议名称: 2007 IEEE/ICME International Conference on Complex Medical Engineering-CME2007(CME2007 第二届国际复合医学工程学术大会)

会议地点: 北京

会议语种:英文

页码: 1536-1539

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）