Epileptic Seizure Detection Using a Convolutional Neural Network

The availability of electroencephalogram (EEG) data has opened up the possibility for new interesting applications, such as epileptic seizure detection. The detection of epileptic activity is usually performed by an expert based on the analysis of the EEG data. This paper shows how a convolutional neural network (CNN) can be applied to EEG images for a full and accurate classification. The proposed methodology was applied on images reflecting the amplitude of the EEG data over all electrodes. Two groups are considered: (a) healthy subjects and (b) epileptic subjects. Classification results show that CNN has a potential in the classification of EEG signals, as well as the detection of epileptic seizures by reaching 99.48% of overall classification accuracy.

[1]  Cunlu Xu,et al.  Road vehicle detection and classification based on Deep Neural Network , 2016, 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS).

[2]  Li Deng,et al.  A tutorial survey of architectures, algorithms, and applications for deep learning , 2014, APSIPA Transactions on Signal and Information Processing.

[3]  Derek C. Rose,et al.  Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.

[4]  Reza Tafreshi,et al.  Automated Real-Time Epileptic Seizure Detection in Scalp EEG Recordings Using an Algorithm Based on Wavelet Packet Transform , 2010, IEEE Transactions on Biomedical Engineering.

[5]  Sridevi V. Sarma,et al.  Physiology of functional and effective networks in epilepsy , 2015, Clinical Neurophysiology.

[6]  Dario Pompili,et al.  Random ensemble learning for EEG classification , 2018, Artif. Intell. Medicine.

[7]  Ali H. Shoeb,et al.  Patient-specific seizure onset detection , 2004, Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  Beatrice Pesquet-Popescu,et al.  Depth video coding based on intra mode inheritance from texture , 2014, APSIPA Transactions on Signal and Information Processing.

[9]  R. Millard,et al.  On using a self-tuning controller for blood pressure regulation during surgery in man. , 1987, Computers in biology and medicine.

[10]  Jean Gotman.  A few thoughts on “What is a seizure?” , 2011, Epilepsy & Behavior.

[11]  Sheng-Fu Liang,et al.  Combination of EEG Complexity and Spectral Analysis for Epilepsy Diagnosis and Seizure Detection , 2010, EURASIP J. Adv. Signal Process..

[12]  Ram Bilas Pachori,et al.  Classification of seizure and seizure-free EEG signals using local binary patterns , 2015, Biomed. Signal Process. Control..

[13]  Bram van Ginneken,et al.  A survey on deep learning in medical image analysis , 2017, Medical Image Anal..

[14]  Lawrence D. Jackel,et al.  Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.

[15]  Bernardete Ribeiro,et al.  Modeling epileptic brain states using EEG spectral analysis and topographic mapping , 2012, Journal of Neuroscience Methods.

[16]  U. Rajendra Acharya,et al.  Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals , 2017, Comput. Biol. Medicine.