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Research Article |

Feature Fusion of Time-frequency and Deep Learning Features for Epileptic Seizure Detection using EEG Signals

Author(s): Seshasai Priya Sadam* and Nalini NJ

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 11, Issue 3

Publisher : FOREX Publication

Published : 23 September 2023

e-ISSN : 2347-470X

Page(s) : 826-835

DOI: https://doi.org/10.37391/ijeer.110329

Abstract

A persistent brain's neurological state is epilepsy, characterised by recurring seizure. Brain electrical activity is measured using EEG signals, which can be used to detect and diagnose significant brain problems such as Epilepsy, Autism, Alzheimer’s etc. However, manual EEG data processing is time-consuming, requires highly skilled clinicians, and is associated with low inter-rater reliability (IRA). A computer-aided diagnosis approach for epileptic seizure detection from multichannel EEG recordings by fusing the time-frequency features and the deep learning features extracted from Convolutional Neural Network-Gated Recurrent Unit (CNN-GRU) model using canonical correlation analysis (CCA) method is provided in this study. Deep Learning features are extracted using CNN-GRU layers, motivated by recent advancements in image classification and optimised for use with EEG data. We have also extracted time-frequency features such as spectral entropies and Sub Band energies from Empirical mode decomposition (EMD) and Hilbert Marginal Spectrum (HMS). We used CHBMIT dataset to carry out the results and showed that the method proposed for fusing the time-frequency features and deep learning has given better performance.

Keywords: EEG, Epilepsy, Feature Fusion, EMD, HMS, CNN-GRU.




Seshasai Priya Sadam*, Research Scholar, Department of Computer Science Engineering, Faculty of Engineering and Technology, Annamalai University, Chidambaram, Tamil Nadu, India; Email: saipriya.509@gmail.com

Nalini NJ, Associate Professor, Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University, Tamil Nadu, India; Email: njncse78@gmail.com

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Seshasai Priya Sadam and Nalini NJ (2023), Feature Fusion of Time-frequency and Deep Learning Features for Epileptic Seizure Detection using EEG Signals. IJEER 11(3), 826-835. DOI: 10.37391/ijeer.110329.