Automated identification of inter-ictal discharges using residual deep learning neural network amidst of various artefacts

Arshpreet Kaur, Vinod Puri, Kumar Shashvat and Ashwani Kumar Maurya

Chaos, Solitons & Fractals, 2022, vol. 156, issue C

Abstract: Visual analysis to identify inter-ictal activity in scalp EEG to support the diagnosis of epilepsy is a challenging task, which is embarked on by an experienced neurologist. Inter-Ictal state is a phase between convolutions (seizures) that are a feature of epilepsy disorder. The objective of this work is to automate the process of identification of inter-ictal activity and to distinguish it from the activity of a controlled patient with and without presence of artifacts

Keywords: Scalogram; Residual Deep Neural Network; EEG; Epilepsy; Classification; Artifacts (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:156:y:2022:i:c:s0960077922000972

DOI: 10.1016/j.chaos.2022.111886

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