Motor imagery based EEG classification by using common spatial patterns and convolutional neural networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

EEG signal processing has been an important and engaging issue over the last three decades. It has been used in the applications ranging from controlling mobile robots to analyzing sleep stages. Previously it was used in the applications of clinical neurology such as detecting epileptic seizure, finding epileptiform discharges, diagnosis of epilepsy, etc. Convolutional Neural Network (CNN) on the other hand is one of the most popular and successful method that has been broadly utilized in machine learning problems such as pattern recognition, image classification and object detection. The proposed study focuses on maximizing the classification performance by combining two of the most successful methods: CSP (Common Spatial Patterns) and CNN. Three different setups have been established in order to observe the changes in the validation accuracy of the classifier. At first, a CNN (four convolution layers and a fully connected layer) structure is trained by feeding the raw data. Secondly, five different filters are applied to the original signal and their outputs are utilized in the training of a CNN having the same structure. Thirdly, the original signal has been transformed via CSP into another space where its spatial features are observed more clearly and then classified by the CNN. It is observed that the combination of CSP and CNN gives the best performance with 93.75% validation accuracy.

Original languageEnglish
Title of host publication2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728110134
DOIs
Publication statusPublished - Apr 2019
Event2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 - Istanbul, Turkey
Duration: 24 Apr 201926 Apr 2019

Publication series

Name2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019

Conference

Conference2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019
Country/TerritoryTurkey
CityIstanbul
Period24/04/1926/04/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Common Spatial Patterns
  • Convolutional Neural Network
  • Deep Learning
  • EEG Motor Imagery

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