[1]张晓楠,刘建平.Graz- 脑机接口研究概述[J].智能系统学报,2013,8(5):395-399.[doi:10.3969/j.issn.1673-4785.201304055]
　ZHANG Xiaonan,LIU Jianping.Summary on the research for Graz-brain-computer interface[J].CAAI Transactions on Intelligent Systems,2013,8(5):395-399.[doi:10.3969/j.issn.1673-4785.201304055]
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Graz- 脑机接口研究概述

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 8 期数: 2013年第5期 页码: 395-399 栏目: 综述 出版日期: 2013-10-25
Title:
Summary on the research for Graz-brain-computer interface
文章编号:
1673-4785(2013)05-0395-05
作者:
张晓楠1，刘建平2
1.武警工程大学 信息工程系，陕西 西安 710086； 2.武警工程大学 理学院，陕西 西安 710086
Author(s):
ZHANG Xiaonan 1, LIU Jianping 2
1.Information Engineering Department, Chinese Armed Police Force Engineering University, Xi’an 710086, China; 2. College of Science, Chinese Armed Police Force Engineering University, Xi’an 710086, China
关键词:
Graz- 脑机接口; 脑机接口; 运动想象控制; μ节律同步; 自适应回归参数; 复杂波段功率特征; 相位同步特征; 自适应分类器
Keywords:
Graz-BCI;  BCI;  control for motion thinking;  μ rhythm synchronization;  adaptive regression parameter;  power feature of complex wave band;  phase synchronization features;  adaptive classifier
分类号:
TP391.4
DOI:
10.3969/j.issn.1673-4785.201304055
文献标志码:
A
摘要:
在明确了BCI相关概念与研究背景的基础上，从Graz-BCI的研究内容和应用2个方面，对Graz-BCI的研究现状进行了概述.归纳了运动想象控制、μ节律同步、自适应回归参数、复杂波段功率特征、相位同步特征及自适应分类器等方面Graz-BCI的关键技术，介绍了运动想象控制的研究基础、试验方法及相关参数、与自适应回归参数匹配的分类器、基于相位的复杂波段功率特征及相位同步特征、ADIM和ALDA 2种自适应分类器.总结了Graz-BCI技术在神经假体与拼写设备的相关应用，指出了Graz-BCI在运动想象控制、“大脑开关”以及光学BCI原理机等方面的发展趋势.
Abstract:
On the basis of defining the related concepts and research background of brain computer interface (BCI), the present research situation of Graz-BCI are summarized from two aspects including both research content and research application. The key technologies of Graz-BCI for such aspects as control for motion thinking, μ rhythm synchronization, adaptive regression parameter, power feature of complex wave band, phase synchronization features and adaptive classifier, are induced. The research basis, test method and related parameters on the control for motion thinking, the classifier matching the adaptive regression parameter, the power feature of complex wave band and phase synchronization features on basis of phase, ADIM (adaptive information matrix) and ALDA (adaptive linear discriminant analysis) adaptive classifier, are introduced. The relevant application of Graz-BCI technology on the aspects of nerve prosthesis and spelling equipment are summarized, in addition, the developing trend of Graz-BCI on such aspects as the control for motion thinking, “brain switch” and the optical BCI prototype machine are pointed out.
参考文献/References:
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备注/Memo

收稿日期：2013-04-17.???? 网络出版日期：2013-09-29. 
通信作者：张晓楠. E-mail:474375299@qq.com.
作者简介：
张晓楠，女，1987年生，硕士研究生，主要研究方向为数字信号处理. 
刘建平，男，1967年生，教授，博士后，武警工程大学军事通信学学科带头人，主要研究方向为数字信号处理.睡眠质量评估方面的研究达到了国际前沿水平，获武警部队科技进步三等奖2项，发表学术论文30余篇，其中被EI检索6篇.

更新日期/Last Update: 2013-11-28
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