Analysis of alpha rhythm epileptic Electroencephalogram based on Inner composition alignment

DOI

10.2991/ameii-16.2016.126How to use a DOI?

Keywords

alpha, rhythm, Electroencephalogram, epileptic, Inner composition alignment

Abstract

The EEG signal is an important tool for the diagnosis and prediction of epilepsy due to EEG containing a large number of physiological and pathological information. Based on alpha rhythm multi-channel EEG (electroencephalogram), this paper applied inner composition alignment (IOTA) algorithm to construct brain functional network and visualize the network topology. It is to apply the algorithm to calculate and analyze IOTA coefficient, the node average degree and clustering coefficient of epileptic brain network for studying if epileptic brain network is significantly different from those of normal. The results show that IOTA coefficient of epileptic brain network obviously differs from the normal by calculating T testing with SPSS software, which proved that the effectiveness of the algorithm to distinguish IOTA coefficient of epileptic brain network.

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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TY  - CONF
AU  - Yiyi He
AU  - Danqin Xing
AU  - Jiaqin Wang
AU  - Jia-Fei Dai
AU  - Jun Wang
AU  - Feng-Zhen Hou
PY  - 2016/04
DA  - 2016/04
TI  - Analysis of alpha rhythm epileptic Electroencephalogram based on Inner composition alignment
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SP  - 633
EP  - 636
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.126
DO  - 10.2991/ameii-16.2016.126
ID  - He2016/04
ER  -