Proceedings of the 2015 International Conference on Computer Science and Intelligent Communication

Detrended Fluctuation Analysis of Acupuncture based on Neural Electrical Signals

Authors
Xiaobin Wang, Yanqiu Che, Chunxiao Han, Yingmei Qin
Corresponding Author
Xiaobin Wang
Available Online July 2015.
DOI
10.2991/csic-15.2015.36How to use a DOI?
Keywords
Acupuncture, EEG, Detrended fluctuation analysis
Abstract

Manual acupuncture (MA) is a traditional Chinese Medicine clinical therapy. Although its effectiveness has been proved by clinical trials over thousands of years, the effect and mechanism of acupuncture on the nervous system is not yet clear.Brain is senior central nervous system, and acupuncture as an external stimulation, can induce various electrical activitiesin the brain cortex.In this paper, we design experiment that acupuncture at acupointZusanli withfour different frequencies, andcollect neural signalson the brain.Detrended fluctuation analysis method is used to extract features from EEG signals evoked by different MA manipulations, which may provide theoretical basis forquantifying acupuncture and revealing the mechanism of acupuncture from the aspect of neural electrical signals.

Copyright
© 2015, 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 2015 International Conference on Computer Science and Intelligent Communication
Series
Advances in Computer Science Research
Publication Date
July 2015
ISBN
978-94-62520-84-4
ISSN
2352-538X
DOI
10.2991/csic-15.2015.36How to use a DOI?
Copyright
© 2015, 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  - Xiaobin Wang
AU  - Yanqiu Che
AU  - Chunxiao Han
AU  - Yingmei Qin
PY  - 2015/07
DA  - 2015/07
TI  - Detrended Fluctuation Analysis of Acupuncture based on Neural Electrical Signals
BT  - Proceedings of the 2015 International Conference on Computer Science and Intelligent Communication
PB  - Atlantis Press
SP  - 152
EP  - 155
SN  - 2352-538X
UR  - https://doi.org/10.2991/csic-15.2015.36
DO  - 10.2991/csic-15.2015.36
ID  - Wang2015/07
ER  -