Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)

Beta wave of sleep electroencephalogram analysis based on sign series entropy

Authors
Min Zhao, Yuting Li, Lu Yang, Jia-Fei Dai, Jun Wang, Feng-Zhen Hou
Corresponding Author
Min Zhao
Available Online April 2016.
DOI
https://doi.org/10.2991/ameii-16.2016.129How to use a DOI?
Keywords
sleep EEG, sign series entropy
Abstract

Sleep and wake EEG have some differences. After studying their brain waves and calculating the sign series entropy, we use the T test for the detection of sleep and wake EEG data to figure out whether they are different. After beta waves being filtered out by the filter, we calculate the entropy of the sign series. The results of T test show that the beta waves in the state of sleep and wake are different.

Copyright
© 2016, 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 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
Series
Advances in Engineering Research
Publication Date
April 2016
ISBN
978-94-6252-188-9
ISSN
2352-5401
DOI
https://doi.org/10.2991/ameii-16.2016.129How to use a DOI?
Copyright
© 2016, 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  - Min Zhao
AU  - Yuting Li
AU  - Lu Yang
AU  - Jia-Fei Dai
AU  - Jun Wang
AU  - Feng-Zhen Hou
PY  - 2016/04
DA  - 2016/04
TI  - Beta wave of sleep electroencephalogram analysis based on sign series entropy
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SP  - 649
EP  - 652
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.129
DO  - https://doi.org/10.2991/ameii-16.2016.129
ID  - Zhao2016/04
ER  -