Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/15284
Title: Independent component analysis, the validation on volume conductor platform and the application in automatic artifacts removal and source locating of egg signals
Authors: CAO CHENG
Keywords: eeg, ICA, LORETA, artifact removal, volume conductor platform
Issue Date: 14-Apr-2006
Source: CAO CHENG (2006-04-14). Independent component analysis, the validation on volume conductor platform and the application in automatic artifacts removal and source locating of egg signals. ScholarBank@NUS Repository.
Abstract: Independent Component Analysis (ICA) is a new and powerful blind signal separation algorithm.In this research, ICA was verified by experiments on a novel volume conductor platform which has similar electrical characteristic and multi-layer structure to the human brain. The result shows that ICA can decompose signals mixed on the human brain with good accuracy. ICA was used to automatically remove ECG and EOG artifacts online in this research. An ICA based Low Resolution Electromagnetic Tomography method (LORETA) was also developed in this research for locating the event stimulated brain activities and spontaneous brain activities from single-trial EEG.
URI: http://scholarbank.nus.edu.sg/handle/10635/15284
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
CaoCheng.pdf4.7 MBAdobe PDF

OPEN

NoneView/Download

Page view(s)

202
checked on Dec 11, 2017

Download(s)

177
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.