Nonlinear Granger causality and its application in the analysis of epileptic EEG and ECG signal

DOI

10.2991/icmse-15.2015.320How to use a DOI?

Keywords

nolinear Granger causality, epileptic, kernel function

Abstract

In this paper, a method based on the nolinear Granger causality is used to analyze epilptic EEG and ECG signal. Polynomial kernel function, Gaussian kernel function and sigmoid kernel function are used to map the linear data in low dimensional input space into high dimensional feature space .In this space linear Granger method can be used to analyse the biomedical signals. The results show that the effect of ECG signals to EEG signals is more significant than that of EEG signals to ECG signals and the result by normal subjects is more significant than that of epileptic subjects. This study is helpful for the analysis of epileptic patient's EEG and ECG signal..

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  - Peng Du
AU  - Jiafei Dai
AU  - Jin Li
AU  - Qianli Mal
PY  - 2015/12
DA  - 2015/12
TI  - Nonlinear Granger causality and its application in the analysis of epileptic EEG and ECG signal
BT  - Proceedings of the 2015 6th International Conference on Manufacturing Science and Engineering
PB  - Atlantis Press
SP  - 1773
EP  - 1776
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-15.2015.320
DO  - 10.2991/icmse-15.2015.320
ID  - Du2015/12
ER  -