Abstract
The process of inspecting electroencephalography (EEG) signals of patients with epilepsy to distinguish between focal and non-focal seizure source is a crucial step prior to surgical interference. In this paper, a deep learning approach using a long short-term memory (LSTM) algorithm is investigated for the purpose of automatic discrimination between focal and non-focal epileptic EEG signals. The study is carried out by acquiring 7500 pairs of x and y EEG channels signals from the publicly available Bern-Barcelona EEG database. The manual classification of each signal type was visually done by two board-certified electroencephalographers and neurologists. Initially, every channel signals are pre-processed using $z$ -score normalization and Savitzky-Golay filtering. The signals are used as inputs to a pre-defined Bi-directional LSTM algorithm for the training process. The classification is performed using a k-fold cross-validation following 4-, 6-, and 10-fold schemes. At the end, the performance of the algorithm is evaluated using several metrics with a complete summary table of the recent state-of-art studies in the field. The developed algorithm achieved an overall Cohen’s kappa $\kappa $ , accuracy, sensitivity, and specificity values of 99.20%, 99.60%, 99.55%. and 99.65%, respectively, using x channels and 10-fold cross-validation scheme. The study pave the ways toward implementing deep learning algorithms for the purpose of EEG signals identification in a clinical environment to overcome human errors resulting from visually inspection.
Highlights
Epilepsy has become a major neurological disorder of the brain that is characterized by the occurrence of repeated seizures
According to the World Health Organization (WHO) [2], more than 50 million people around the world are suffering from epileptic seizures, where as 80% among them are living in low- and middle-income countries
A sample from the non-focal EEG signals is shown in Fig. 4 before and after the pre-processing steps
Summary
Epilepsy has become a major neurological disorder of the brain that is characterized by the occurrence of repeated seizures. In a case of an epileptic seizure, these electrical waves are disrupted resulting in an imbalanced reactions from the body [1]. Non-focal epilepsy affects multiple areas within the brain even though they were not affected directly by the seizures [1], [3]. The majority of epileptic patients (60%) become pharmacoresistant, that is not responding to medications. They require surgical interference to treat the seizures [4]. The precise localization of seizure areas is important prior to the surgery to reduce the risks accompanied with invasive interference with the brain
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