Classification of P300 event-related potentials using wavelet transform, MLP, and soft margin SVM

Handayani Tjandrasa*, Supeno Djanali

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

Brain-computer interface is a communication mechanism between EEG signals and a computer, such that the system can capture the brain intention without involving motoric and muscular neurons. This study utilized the EEG recordings of four disabled subjects during repeated stimuli using a six-choice P300 paradigm. The EEG signals were processed with a Butterworth bandpass filter and Wavelet Transform, divided into two categories of the target and non-target trials. The EEG data were improved by removing the high amplitude fluctuation of the signals around the end of each file. The Wavelet Transform was implemented using Stationary Wavelet Transform (SWT) and Discrete Wavelet Transform (DWT). The target and non-target trials were averaged for every five trials, and the averaged non-target trials were reduced further by selecting one of every five consecutive data. The reduced target and non-target trial data were classified using multilayer perceptron and support vector machine. Using SWT, multilayer perceptron gave the maximum accuracy, sensitivity, and specificity of 96.4%, 96.6%, 96.2% respectively, and support vector machine obtained the maximum accuracy of 98.2%, sensitivity of 100%, and specificity of 96.4%. While using DWT, the best performance of multilayer perceptron gave the accuracy, sensitivity, and specificity of 94.5%, 100%, 89.3% respectively, and support vector machine had the maximum accuracy of 98.2%, sensitivity of 96.4%, and specificity of 100%.

Original languageEnglish
Title of host publicationProceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages343-347
Number of pages5
ISBN (Electronic)9781538643624
DOIs
Publication statusPublished - 8 Jun 2018
Event10th International Conference on Advanced Computational Intelligence, ICACI 2018 - Xiamen, Fujian, China
Duration: 29 Mar 201831 Mar 2018

Publication series

NameProceedings - 2018 10th International Conference on Advanced Computational Intelligence, ICACI 2018

Conference

Conference10th International Conference on Advanced Computational Intelligence, ICACI 2018
Country/TerritoryChina
CityXiamen, Fujian
Period29/03/1831/03/18

Keywords

  • Discrete wavelet transform
  • EEG
  • Multilayer perceptron
  • P300 event-related potential
  • Soft margin support vector machine
  • Stationary wavelet transform

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