Attention state analysis based on the improved k nearest neighbour network

DOI

10.2991/icmse-15.2015.321How to use a DOI?

Keywords

complex network, time series, epilepsy.

Abstract

In this paper, a method of analysis attention state based on the time series transformed by the improved k nearest neighbour network is proposed. In the proposed method, counting number state EEG signals and closing eyes state EEG signals are constructed into networks by the improved k nearest neighbour network respectively, and each networks are converted into time series, which are compared with original EEG time series by means of analysis of power spectrum. The results show that studying power spectrum of time series from network is more easily than original time series to distinguish between counting number state EEG signals and closing eyes state EEG signals. We confirmed that the proposed method could be of practical use.

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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TY  - CONF
AU  - Chengcheng Liu
AU  - Xiaolin Huang
AU  - Jin Li
AU  - Qianli Ma
PY  - 2015/12
DA  - 2015/12
TI  - Attention state analysis based on the improved k nearest neighbour network
BT  - Proceedings of the 2015 6th International Conference on Manufacturing Science and Engineering
PB  - Atlantis Press
SP  - 1777
EP  - 1780
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-15.2015.321
DO  - 10.2991/icmse-15.2015.321
ID  - Liu2015/12
ER  -