Scalp electroencephalography (sEEG) based advanced prediction of epileptic seizure time and identification of epileptogenic region.

Scalp electroencephalography (sEEG) based advanced prediction of epileptic seizure time and identification of epileptogenic region. Biomed Tech (Berl). 2020 Jul 05;: Authors: Sharma A, Rai JK, Tewari RP Abstract Objectives Epilepsy is characterized by uncontrollable seizure during which consciousness of patient is disturbed. Prediction of the seizure in advance will increase the remedial possibilities for the patients suffering from epilepsy. An automated system for seizure prediction is important for seizure enactment, prevention of sudden unexpected deaths and to avoid seizure related injuries. Methods This paper proposes the prediction of an upcoming seizure by analyzing the 23 channel non-stationary EEG signal. EEG signal is divided into smaller segments to change it into quasi-stationary data using an overlapping moving window. Brain region is marked into four regions namely left hemisphere, right hemisphere, central region and temporal region to identify the epileptogenic region. The epileptogenic region shows significant variations during pre-ictal state in comparison to the other regions. So, seizure prediction is carried out by analyzing EEG signals from this region. Seizure prediction is proposed using features extracted from both time and frequency domain. Relative entropy and relative energy are extracted from wavelet transform and Pearson correlation coefficient is obtained from time domain EEG signal. Extracted features...
Source: Biomedizinische Technik/Biomedical Engineering - Category: Biomedical Engineering Tags: Biomed Tech (Berl) Source Type: research