Design of BCI Motor Imagery Classification Using WPT-CSP and CNN

Dio Alif Pradana, Basari

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

Abstract

This study proposes a new method in an electroencephalograph (EEG)-based Brain-Computer Interface (BCI) that can directly utilize brain signals to control external devices. The motor Imagery (MI) signal, which contains an image of a certain limb movement, is generally used in BCI. It does not need direct movements. The implementation of MI-EEG signal into BCI still experiences major issues because the patterns obtained for each recording can vary from one another even though they have the same type of motion. In this study, we utilized the Wavelet Packet Transform (WPT) method to decompose the EEG signal into specific sub-band frequencies and Common Spatial Pattern (CSP) as a spatial filter to increase the spatial resolution of the EEG signal. The Convolutional Neural Network (CNN) was subsequently selected for training from the classifier. Next, the results of the training were used to classify the movements of the given MI-EEG. We evaluated the model using dataset 2a from Brain-Computer Interface Competition (BCIC) IV. The results of this method showed the increase in the accuracy of 32% and in Kappa up to 0.42 and the decrease in Root Mean Square Error (RMSE) up to 1.21, compared with only using CNN as the classifier. These results showed fairly good performance compared to other methods used previously in dataset 2a from BCIC IV.

Original languageEnglish
Title of host publication6th Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices
Subtitle of host publicationProceedings of the 6th International Symposium of Biomedical Engineering, ISBE 2021
EditorsSiti Fauziyah Rahman, Ahmad Zakiyuddin, Yudan Whulanza, Nurul Intan
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735443716
DOIs
Publication statusPublished - 16 Aug 2022
Event6th International Symposium of Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices, ISBE 2021 - Depok, Virtual, Indonesia
Duration: 7 Jul 20218 Jul 2021

Publication series

NameAIP Conference Proceedings
Volume2537
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference6th International Symposium of Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices, ISBE 2021
Country/TerritoryIndonesia
CityDepok, Virtual
Period7/07/218/07/21

Keywords

  • Accuracy
  • CNN
  • CSP
  • Kappa
  • MI-EEG
  • RMSE
  • Spatial Resolution
  • WPT

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