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

Abdi-Sargezeh, B ORCID: https://orcid.org/0000-0003-1141-0702 and Sanei, S ORCID: https://orcid.org/0000-0002-3437-2801, 2021. Advances in epilepsy monitoring by detection and analysis of brain epileptiform discharges. Psychology and Neuroscience. ISSN 1984-3054

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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.

Item Type:	Journal article
Publication Title:	Psychology and Neuroscience
Creators:	Abdi-Sargezeh, B. and Sanei, S.
Publisher:	American Psychological Association (APA)
Date:	21 October 2021
ISSN:	1984-3054
Identifiers:	Number Type 10.1037/pne0000275 DOI 1482353 Other
Rights:	©American Psychological Association, 2021. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. The final article is available, upon publication, at: https://doi.org/10.1037/pne0000275
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Ward
Date Added:	29 Oct 2021 13:14
Last Modified:	31 Jan 2022 14:01
URI:	https://irep.ntu.ac.uk/id/eprint/44545

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