Amazing technological breakthrough possible @S-Logix

Office Address

  • #5, First Floor, 4th Street Dr. Subbarayan Nagar Kodambakkam, Chennai-600 024 Landmark : Samiyar Madam
  • +91- 81240 01111

Social List

Epileptic Seizure Detection using Deep Convolutional Autoencoder - 2018

Epileptic Seizure Detection Using Deep Convolutional Autoencoder

Research Paper on Epileptic Seizure Detection Using Deep Convolutional Autoencoder

Research Area:  Machine Learning


Monitoring and recording brain activities using Electroencephalograms (EEGs) has become the foremost wide applied tool by physicians for epilepsy diagnosis due to viable reasons like its availability, simplicity, and low cost. In this paper, we propose an automatic epileptic seizure detection framework based on deep learning techniques that are applied to raw EEG signals recordings without the overhead of features extraction. The proposed framework uses one-dimensional deep convolutional autoencoder for features extraction and dimensionality reduction. Three different neural networks systems classifiers are evaluated. Classification between normal and ictal cases has achieved 100% accuracy on all systems. The best classification results between the normal, interictal and ictal cases accomplished a 99.33% average overall accuracy using Bidirectional Long Short-Term Memory.

Epileptic Seizure Detection
Deep Convolutional Autoencoder
neural networks
Long Short-Term Memory
Machine Learning
Deep Learning

Author(s) Name:  Ahmed M. Abdelhameed; Hisham G. Daoud; Magdy Bayoumi

Journal name:  

Conferrence name:  IEEE International Workshop on Signal Processing Systems (SiPS)

Publisher name:  IEEE

DOI:  10.1109/SiPS.2018.8598447

Volume Information: