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

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...

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Bibliographic Details
Published in2021 29th European Signal Processing Conference (EUSIPCO) pp. 1167 - 1171
Main Authors Abdi-Sargezeh, Bahman, Valentin, Antonio, Alarcon, Gonzalo, Sanei, Saeid
Format Conference Proceeding
LanguageEnglish
Published EURASIP 23.08.2021
Subjects
Epilepsy
Epileptiform discharges
Europe
IED morphology
intracranial EEG
Morphology
Shape
Signal processing
spatial components
tensor decomposition
Tensors
Training
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ISSN2076-1465
DOI10.23919/EUSIPCO54536.2021.9616233

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Summary: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.
ISSN:2076-1465
DOI:10.23919/EUSIPCO54536.2021.9616233