EEG-Based Cognitive Interfaces for Ubiquitous Applications: Developments and Challenges

被引：47

作者：

Hu, Bin ^{[1
,2
]}

Majoe, Dennis ^{[3
]}

Ratcliffe, Martyn ^{[4
]}

Qi, Yanbing ^{[2
]}

Zhao, Qinglin ^{[2
]}

Peng, Hong ^{[2
]}

Fan, Dangping ^{[2
]}

Zheng, Fang ^{[2
]}

Jackson, Mike ^{[5
]}

Moore, Philip ^{[1
]}

机构：

[1] Birmingham City Univ, Intelligent Contextual Comp Grp, Pervas Comp Ctr, Birmingham, W Midlands, England

[2] Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China

[3] ETH, Inst Comp Syst, Zurich, Switzerland

[4] Birmingham City Univ, Sch Comp Telecommun & Networks CTN, Birmingham, W Midlands, England

[5] Birmingham City Univ, Sch Business, Birmingham, W Midlands, England

来源：

IEEE INTELLIGENT SYSTEMS | 2011年 / 26卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Electroencephalography; Feature extraction; Noise reduction; Frequency domain analysis; User interfaces; Brain models; Neuroscience; Ubiquitous computing; ubiquitous computing; Intelligent Systems; brain informatics; EEG; cognitive interface; FRONTAL ELECTROENCEPHALOGRAPHIC ASYMMETRY; DEPRESSION; STRESS; COMPLEXITY; STABILITY; ANXIETY; LONG;

D O I：

10.1109/MIS.2011.58

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Technical advances in the neuroelectric recordings and in the computational tools for the analysis of the brain activity and connectivity make it now possible to follow and to quantify, in real time, the interactive brain activity in a group of subjects engaged in social interactions. The degree of interaction between persons can then be assessed by reading" their neuroelectric activities. Imaging the social brain can thus open a new area of study in neuroscience. © 2011 IEEE."

引用

页码：46 / 53

页数：8

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