Automatically Extract P300 Within Several Trials from EEG Based on ICA

CHEN Hong-bo; LI Bei-lei; CHEN Zhen-cheng

doi:10.3969/j.issn.0372-2112.2012.06.032

您当前的位置：

首页 >

文章列表页 >

Automatically Extract P300 Within Several Trials from EEG Based on ICA

更新时间：2025-07-16

- Automatically Extract P300 Within Several Trials from EEG Based on ICA
- Acta Electronica Sinica Vol. 40, Issue 6, Pages: 1257-1262(2012)
- 作者机构：
  
  1. 桂林电子科技大学生命与环境科学学院,广西,桂林,541004
  2. 桂林电子科技大学电子工程与自动化学院,广西,桂林,541004
  3. 桂林电子科技大学生命与环境科学学院广西桂林,541004
  4. 桂林电子科技大学电子工程与自动化学院广西桂林,541004
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2012.06.032
  CLC： R318.04TP391
- Published：2012
- 稿件说明：
移动端阅览
CHEN Hong-bo, LI Bei-lei, CHEN Zhen-cheng. Automatically Extract P300 Within Several Trials from EEG Based on ICA[J]. Acta Electronica Sinica, 2012, 40(6): 1257-1262.
DOI：

CHEN Hong-bo, LI Bei-lei, CHEN Zhen-cheng. Automatically Extract P300 Within Several Trials from EEG Based on ICA[J]. Acta Electronica Sinica, 2012, 40(6): 1257-1262. DOI： 10.3969/j.issn.0372-2112.2012.06.032.

摘要

提出一种基于Infomax ICA少次自动提取脑电信号P300成分的方法.为了提高ICA分解的有效性

对原始数据中的自发脑电信号和P300成分进行了均衡.混合信号经过ICA分解后

根据IC的固定时间模式的标准差来自动选择P300成分IC

最后重构得到P300成分.实验结果是:利用6试次实验数据经过本文方法处理后能自动得到P300成分

与29试次平均结果(标准信号)相比

它们之间的Pearson相关系数达0.9035

而6试次实验数据平均的结果与标准信号之间的Pearson相关系数为0.5105.结果表明

该方法能有效的获取P300成分

同时增强了P300成分少次提取的客观性.

Abstract

This paper puts forward a method for automatically extracting the P300 from electroencephalography (EEG) signals within several trials based on Infomax independent component analysis (ICA).An algorithm for signaling equilibrium is proposed to enhance the effectiveness of ICA decomposition.After the mixed signal is decomposed by Infomax ICA

the independent component (IC) of P300 is automatically selected according to the standard deviation of the fixed-temporal-pattern of the IC

and applied in P300 reconstruction.Experimental results show that the P300 can be obtained automatically after six trials on the experimental data

and the result of its Pearson correlation coefficient (PCC) within the average of 29 trials (standard signal) is 0.9035.However

the PCC of the average result of six trials and standard signal is only 0.5105

demonstrating the practical applicability of Infomax ICA.This algorithm enhances the objectivity of P300 extraction within several trials.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A Virtual Chinese Keyboard BCI System Based on P300 Potentials

Fast-ICA Based Blind Estimation of Spreading and Information Sequences of Short-Code CDMA Signals in Synchronous and Asynchronous Systems

Gene Clustering Based on Genetic Algorithm

A Hybrid BCI Based on the Combination of SSVEP Blocking and P300 Features

Related Author

ZHENG Xiao-xiang

CHENG Wei-dong

ZHANG Ji-cai

LI Xin

ZHANG Jian-hui

SU Yu

WU Bian

LU Feng-bo

Related Institution

Qiushi Academy for Advanced Studies,Zhejiang University

College of Computer Science,Zhejiang University

College of Biomedical Engineering and Instrument Science,Zhejiang University

Qiushi Academy for Advanced StudiesZhejiang UniversityHangzhouZhejiang 310027China

College of Computer ScienceZhejiang UniversityHangzhouZhejiang 310027China

⁰