Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

Multiscale Symbolic Transfer Entropy on Closing Eyes and Being Idle in rhythm of Electroencephalogram

Authors
Lizhao DU, Wenpo YAO, Xiaolin HUANG, Jun WANG
Corresponding Author
Lizhao DU
Available Online July 2017.
DOI
10.2991/eia-17.2017.45How to use a DOI?
Keywords
multiscale symbolic transfer entropy(MSTE); electroencephalogram (EEG); closing eyes; being idle
Abstract

As we all know, electroencephalogram (EEG) is an effective tool to analyze many disease, epilepsy, for example. According to the latest research, we have found out that the value of multiscale symbolic transfer entropy (MSTE) on closing eyes and being idle differs but there is a question still, what exactly makes this difference? Therefore, we analyze different rhythm of EEG and finally we draw this conclusion: the value of MSTE on closing eyes and being idle differs exactly in the rhythm of EEG. With this conclusion, we can catch the dynamic information much more convenient and accurately.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
Series
Advances in Intelligent Systems Research
Publication Date
July 2017
ISBN
10.2991/eia-17.2017.45
ISSN
1951-6851
DOI
10.2991/eia-17.2017.45How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lizhao DU
AU  - Wenpo YAO
AU  - Xiaolin HUANG
AU  - Jun WANG
PY  - 2017/07
DA  - 2017/07
TI  - Multiscale Symbolic Transfer Entropy on Closing Eyes and Being Idle in rhythm of Electroencephalogram
BT  - Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
PB  - Atlantis Press
SP  - 209
EP  - 211
SN  - 1951-6851
UR  - https://doi.org/10.2991/eia-17.2017.45
DO  - 10.2991/eia-17.2017.45
ID  - DU2017/07
ER  -