Early Detection Of Epilepsy Based On Synchronization Degree

Authors

  • YN Baakek Biomedical Engineering Laboratory (GBM), Biomedical Engineering Department, Faculty of Technology, Tlemcen University, B.P.119 (13000), Algeria Author
  • SM Debbal Biomedical Engineering Laboratory (GBM), Biomedical Engineering Department, Faculty of Technology, Tlemcen University, B.P.119 (13000), Algeria Author

DOI:

https://doi.org/10.47363/JMHC/2020(2)133

Keywords:

Electroencephalogram Signal, Bispectral Analysis, Degree Of Synchronization, Normal Case

Abstract

In this work, the synchronization degree is calculated using bi-spectral analysis in order to distinguish between three sets of electroencephalogram signals: normal, pre-ictal, and epileptic seizure cases. The obtained results are compared to six parameters which also extracted from the same analysis; such as the entropies, the mean of bi-spectral amplitude, and weighted center of the bi-spectrum. The obtained results using the proposed algorithm are very satisfactory compared to the other parameters, and show that the synchronization is high in normal cases, zero in pre-ictal cases, and low in epileptic cases, and it confirms the efficiency of the proposed algorithm

Author Biographies

  • YN Baakek, Biomedical Engineering Laboratory (GBM), Biomedical Engineering Department, Faculty of Technology, Tlemcen University, B.P.119 (13000), Algeria

    Biomedical Engineering Laboratory (GBM), Biomedical Engineering Department, Faculty of Technology, Tlemcen University, B.P.119 (13000), Algeria 

  • SM Debbal, Biomedical Engineering Laboratory (GBM), Biomedical Engineering Department, Faculty of Technology, Tlemcen University, B.P.119 (13000), Algeria

    Biomedical Engineering Laboratory (GBM), Biomedical Engineering Department, Faculty of Technology, Tlemcen University, B.P.119 (13000), Algeria 

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Published

2020-11-07

Issue

Vol. 2 No. 4 (2020): Volume 2 Issue 4

Section

Articles