Analysis of Dimension Reduction by PCA and AdaBoost on Spelling Paradigm EEG Data

被引：0

作者：

Yildirim, Asil ^{[1
]}

Halici, Ugur ^{[1
]}

机构：

[1] Middle E Tech Univ, Dept Elect & Elect Engn, METU VIS LAB, TR-06531 Ankara, Turkey

来源：

PROCEEDINGS OF THE 2013 6TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI 2013), VOLS 1 AND 2 | 2013年

关键词：

Brain Computer Interfaces; Spelling Paradigm; Principal Component Analysis; Adaboost; Support Vector Machine; BCI COMPETITION 2003; MENTAL PROSTHESIS;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Spelling Paradigm is a BCI application which aims to construct words by finding letters using P300 signals recorded via channel electrodes attached to the diverse points of the scalp. In this study effects of dimension reduction using Principal Component Analysis (PCA) and AdaBoost methods on time domain characteristics of P300 evoked potentials in Spelling Paradigm are analyzed. Support Vector Machine (SVM) is used for classification.

引用

页码：192 / 196

页数：5

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