Focal Non-Specific Seizure Classification Based on EEG Signal Using Artificial Neural Network Method

Authors

  • Siti Rizqia Solihati Suhermawan Telkom University
  • Raditiana Patmasari Telkom University
  • Sugondo Hadiyoso Telkom University

Abstract

Abstract—In EEG signals Epilepsy has various signals. One of them is Focal Non-Specific Seizure which has features that are different from other signals. This paper will detect the presence of a signal surge in the Focal Non-Specific Seizure. This detection is based on brain activity using Epilepsy EEG which will be compared with normal people's training data. Focal Non-Specific Seizure Signals will go through the preprocessing process. Then the preprocessing results are feature extraction with Independent Component Analysis (ICA) which will then be classified with Artificial Neural Networks (ANN). From this study the greatest accuracy of one of the characteristics is weight vactor of 90%.

Keywords— Focal Non-Specific Seizure, Independent Component Analysis (ICA), Artificial Neural Network (ANN)

Downloads

Published

2018-12-20

Issue

No. 2 (2018): Symposium of Future Telecommunication and Technologies (SOFTT) 2018

Section

Articles