Title: An effective algorithm to measure the loss of consciousness degree in epileptic seizure

Authors: Yettou Nour El Houda Baakek; Sidi Mohammed Debbal

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

Abstract: In this work, a new algorithm is developed to measure the loss of consciousness degrees in normal, pre-ictal, and epileptic seizure cases using bi-spectral analysis. The study is carried out on the electroencephalogram (EEG) signals; in which 200 records are used as pre-ictal cases, and 100 records are used as epileptic cases. All these cases are compared to 100 normal cases which represent the EEG signal in relaxed and in an awake state with open eyes. The obtained results are very satisfactory and show the efficiency of the proposed algorithm. The unconsciousness degree is very low in normal cases, very high in pre-ictal cases, and varies between high to middle during epileptic seizure cases. The algorithm promising for studying the unconsciousness degree in other cases such as anaesthesia and in hypnosis cases.

Keywords: EEG signal; loss of consciousness degree; normal cases; pre-ictal cases; epileptic cases; bi-spectral analysis.

DOI: 10.1504/IJMEI.2021.114887

International Journal of Medical Engineering and Informatics, 2021 Vol.13 No.3, pp.200 - 212

Received: 22 Nov 2018
Accepted: 24 Apr 2019
Published online: 11 May 2021 *

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