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基于皮层慢电位的自发脑电实验设计与研究

Experimental Design and Research on Using Slow Cortical Potentials for Brain Computer Interface Based on Spontaneous EEG
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摘要 针对基于自发脑电信号的脑机接口研究,设计了一种科学的且易实现的运动想象实验范例,利用运动想象脑电作为BCI的控制信号。该实验方案能有效地获得可识别的、具有特征性的自发脑电,满足脑机接口实验要求,为BCI的研究提供了一种更加自然、更加实用的控制方式。 This paper designs an scientific experimental paradigm of brain computer interface based on spontaneous electroencephalography which is produced by motor imagination and used as the control signal. This design is easy-realized and can collect the identifiable spontaneous EEG which has some features after processed. It meets the requirements of BCI experiment and supplies a more natural and practical control mode for BCI research.
作者 吴婷 汤学华 杜伟明 孙虹
机构地区 上海电机学院机械学院 安徽建筑工业学院机械与电气工程学院
出处 《上海电机学院学报》 2008年第4期260-263,267,共5页 Journal of Shanghai Dianji University
关键词 自发 脑电信号 脑机接口 运动想象 spontaneous electroencephalography （EEG） brain computer interface motor imagination
分类号 R318 [医药卫生—生物医学工程]
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参考文献10

  • 1Millán J.Adaptive Brain Interfaces[].Communica-tions of ACM.2003
  • 2Millán J,Mouri o J.Asynchronous BCI and LocalNeural Classifiers:an Overview of the Adaptive BrainInterface Project[].IEEE Transaction on NeuralSystem and Rehabilitation Engineering.2003
  • 3Birbaumer N.Brain-computer-interface Research:Coming of Age[].Clinical Neurophysiology.2006
  • 4Schroder M,Bogdan M,Hinterberger T,et al.Au-tomated EEG Feature Selection for Brain ComputerInterfaces[].Conference Proceedings First Inter-nationd IEEE EMBS Conforence on Neural Engineer-ing.2003
  • 5McFarland D J,Wolpaw J R.Sensorimotor rhythm-based Brain-computer Interface(BCI):Feature Selec-tion by Regression Improves Performance[].IEEETransactions on Neural Systems and RehabilitationEngineering.2005
  • 6Christoph Guger,Alois Schlogl,Christa Neuper, et al.Rapid Prototyping of an EEG-Based Brain-Computer Interface (BCI)[].IEEE Transactions on Neural Systern and rehabilitation Engineering.2001
  • 7Lal,TN,Schroder,M,Hinterberger,T,Weston,J,Bogdan,M,Birbaumer,N.Support vector channel selection in BCI[].IEEE Transactions on Biomedical Engineering.2004
  • 8Pfurtscheller G,et al.Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters[].IEEE Transactions on Rehabilitation Engineering.1998
  • 9D Garrett,D A Peterson,C W Anderson et al.Comparison of Linear,Nonlinear,and Feature Selection Methods for EEG Signal Classifi-cation[].IEEE Trans Neural Syst Rehab Eng.2003
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上海电机学院学报
2008年 第4期

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