Advances in epilepsy monitoring by detection and analysis of brain epileptiform discharges.

Abstract

Brain interictal and pre-ictal epileptiform discharges (EDs) are transient events occurred between two or before seizure onsets visible in intracranial electroencephalographs. In the diagnosis of epilepsy and localization of seizure sources, both interictal and ictal recordings are extremely informative. For this propose, computerized intelligent spike and seizure detection techniques have been researched and are constantly improving. This is not only to detect more EDs from over the scalp but also to classify epileptic and non-epileptic discharges. Tensor factorization and deep learning are two advanced and powerful techniques which have been recently suggested for ED detection. Here, our main contribution is to review recent ED detection methods with emphasis on multi-way analysis and deep learning approaches. These techniques have opened a new window to the epilepsy diagnosis and management spheres.

EEG-to-EEG: Scalp-to-Intracranial EEG Translation using a Combination of Variational Autoencoder and Generative Adversarial Networks

“…IEDs are transient activities distinguishable from the background activity, and appear in the form of sharp waves, spikes, or poly-spikes often followed by an inhibitory damped oscillation [4], [5]. However, the sEEG is unable to capture IED signatures, and a large proportion of which is invisible over the scalp [6]- [9]. Only 9% and 22% of IEDs can be visualized from the sEEG recordings respectively in Nayak et al [8] and Yamazaki et al [9] studies.…”

Mapping Scalp to Intracranial EEG using Generative Adversarial Networks for Automatically Detecting Interictal Epileptiform Discharges

“…We aim to apply our model to the concurrent sEEG and iEEG signals recorded from patients suffering from epilepsy. The signals include interictal epileptiform discharges (IEDs), transient activities occurring between two seizure onsets [10]. In terms of morphology, IEDs appear in spikes, poly spikes, or sharp waves, followed by slow waves [11].…”

Sparse Common Feature Analysis for Detection of Interictal Epileptiform Discharges From Concurrent Scalp EEG

“…Epilepsy is a chronic brain disorder that can affect people at any age [1]. It causes recurrent and erratic interruptions in brain functionality, called epileptic seizure, arising due to dysfunction of the brain electrophysiological system and uncontrolled electrical discharges in a group of neurons in the cerebral cortex [2], [3]. Between two seizure onsets, abnormal patterns occur, called interictal epileptiform discharges (IEDs), which can be captured by the EEG [4].…”