Detection of Brain Interictal Epileptiform Discharges from Intracranial EEG by Exploiting their Morphology in the Tensor Structure

Bahman Abdi-Sargezeh, Antonio Valentin, Gonzalo Alarcon, Saeid Sanei

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

4 Citations (Scopus)

Abstract

Detection of interictal epileptiform discharges (IEDs) from EEG signals is the mainstay of diagnosis of epilepsy. The diversity in IED morphologies and their weakness deteriorate the detection performance particularly when the IEDs of different subjects are combined for training. Here, we propose an IED detection system based on tensor factorization in which IEDs with similar morphology are concatenated into the same slice of a tensor. Applying the proposed method to the intracranial EEG 92.9% accuracy has been achieved. This shows that incorporating IED shape diversity into tensor factorization considerably improves the results.

Original languageEnglish
Title of host publication29th European Signal Processing Conference, EUSIPCO 2021 - Proceedings
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages1167-1171
Number of pages5
ISBN (Electronic)9789082797060
DOIs
Publication statusPublished - 2021
Event29th European Signal Processing Conference, EUSIPCO 2021 - Dublin, Ireland
Duration: 23 Aug 202127 Aug 2021

Publication series

NameEuropean Signal Processing Conference
Volume2021-August
ISSN (Print)2219-5491

Conference

Conference29th European Signal Processing Conference, EUSIPCO 2021
Country/TerritoryIreland
CityDublin
Period23/08/202127/08/2021

Keywords

  • Epileptiform discharges
  • IED morphology
  • Intracranial EEG
  • Spatial components
  • Tensor decomposition

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