Analysis of Epileptic and Normal EEG Signals based on Random Walk

DOI

10.2991/eeeis-17.2017.53How to use a DOI?

Keywords

random walk, Bayesian inference, epilepsy, EEG signal

Abstract

In this paper, a random walk model was established for the EEG signal. The characteristic parameters qt and at were extracted from the original EEG signal by Bayesian inference method. By comparing the global maximum of the autocorrelation function of the characteristic parameter qt between patients with epilepsy and normal subjects, this paper obtained the following conclusion, the global maximum of the autocorrelation function of the characteristic parameter qt of EEG signal extracted in epilepsy patients is larger than the normal human in the general trend; and the fluctuation of the global maximum of the autocorrelation function in epilepsy patients is also greater, which suggests that the use of random walk model to analyze the EEG signal can be found the difference in patients with epilepsy and normal subjects; therefore, random walk model can be used to analyze the difference between epileptic EEG signal and normal human EEG signals.

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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TY  - CONF
AU  - Jun MIN
AU  - Jun WANG
PY  - 2017/09
DA  - 2017/09
TI  - Analysis of Epileptic and Normal EEG Signals based on Random Walk
BT  - Proceedings of the 3rd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2017)
PB  - Atlantis Press
SP  - 379
EP  - 384
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-17.2017.53
DO  - 10.2991/eeeis-17.2017.53
ID  - MIN2017/09
ER  -