Nonconvulsive Epileptic Seizure Detection in Scalp EEG Using Multiway Data Analysis


Nonconvulsive status epilepticus is a condition where the patient is exposed to abnormally prolonged epileptic seizures without evident physical symptoms. Since these continuous seizures may cause permanent brain damage, it constitutes a medical emergency. This paper proposes a method to detect nonconvulsive seizures for a further nonconvulsive status epilepticus diagnosis. To differentiate between the normal and seizure electroencephalogram (EEG), a K-Nearest Neighbor, a Radial Basis Support Vector Machine, and a Linear Discriminant Analysis classifier are used. The classifier features are obtained from the Canonical Polyadic Decomposition (CPD) and Block Term Decomposition (BTD) of the EEG data represented as third order tensor. To expand the EEG into a tensor, Wavelet or Hilbert-Huang transform are used. The algorithm is tested on a scalp EEG database of 139 seizures of different duration. The experimental results suggest that a Hilbert-Huang tensor representation and the CPD analysis provide the most suitable framework for nonconvulsive seizure detection. The Radial Basis Support Vector Machine classifier shows the best performance with sensitivity, specificity, and accuracy values over 98%. A rough comparison with other methods proposed in the literature shows the superior performance of the proposed method for nonconvulsive epileptic seizure detection.

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Divisions: College of Health & Life Sciences > School of Optometry > Audiology
College of Health & Life Sciences
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Uncontrolled Keywords: Hilbert Huang Transform,Multiway Data Analysis,Nonconvulsive epileptic seizures,Wavelet Transform,Biotechnology,Computer Science Applications,Electrical and Electronic Engineering,Health Information Management
Publication ISSN: 2168-2194
Last Modified: 30 May 2024 07:14
Date Deposited: 14 Jun 2018 14:20
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2019-03-01
Published Online Date: 2018-04-27
Accepted Date: 2018-04-26
Authors: Aldana, Yissel Rodríguez
Hunyadi, Borbála
Reyes, Enrique J.Marañón
Rodríguez, Valia Rodríguez (ORCID Profile 0000-0002-6085-285X)
Van Huffel, Sabine



Version: Accepted Version

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