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2007 Frontiers in the Convergence of Bioscience and Information Technologies
On the Use of Rough Sets for Artefact Extraction from EEG Datasets
Jeju Island, Korea
October 11-October 13
ISBN: 978-0-7695-2999-8
ASCII Text
x 
 
Kenneth Revett, "On the Use of Rough Sets for Artefact Extraction from EEG Datasets," Frontiers in the Convergence of Bioscience and Information Technologies, pp. 425-430, 2007 Frontiers in the Convergence of Bioscience and Information Technologies, 2007.
 
 
BibTex
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@article{ 10.1109/FBIT.2007.144,
author = {Kenneth Revett},
title = {On the Use of Rough Sets for Artefact Extraction from EEG Datasets},
journal ={Frontiers in the Convergence of Bioscience and Information Technologies},
volume = {0},
year = {2007},
isbn = {978-0-7695-2999-8},
pages = {425-430},
doi = {http://doi.ieeecomputersociety.org/10.1109/FBIT.2007.144},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Frontiers in the Convergence of Bioscience and Information Technologies
TI - On the Use of Rough Sets for Artefact Extraction from EEG Datasets
SN - 978-0-7695-2999-8
SP425
EP430
A1 - Kenneth Revett,
PY - 2007
VL - 0
JA - Frontiers in the Convergence of Bioscience and Information Technologies
ER -
 
High-density electroencephalography produces large volumes of data. The analysis of EEG data is confounded by the existed of a number of different artefacts such as eye blink and, muscle movement which impede the analysis of the data. Typically, artefacts are removed by visual inspection ­ an arduous task for high-density recordings. In addition, different researchers use Consistency across different laboratories is often difficult, and in addition, the task has to be repeated for each study. An automated method for artefact identification and removal would be a very useful tool for data processing in this domain. In this study, rough sets is employed as a means of automating artefact identification and removal within the context of EEG analysis using the EEGLAB analysis system. The results from this preliminary study indicate that artefacts can be identified and removed with approximately 85% accuracy.
Citation:
Kenneth Revett, "On the Use of Rough Sets for Artefact Extraction from EEG Datasets," fbit, pp.425-430, 2007 Frontiers in the Convergence of Bioscience and Information Technologies, 2007
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