Classification of P300 in EEG signals for disable subjects using singular spectrum analysis

Handayani Tjandrasa, Supeno Djanali, F. X. Arunanto

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

2 Citations (Scopus)

Abstract

Brain-computer interfaces have been enabled severely disabled users to communicate with their environments. One method is to use a controlled stimulus to elicit the P300 event-related potential. EEG signals during the repeated stimuli were recorded from four disabled subjects and processed with a Butterworth bandpass filter and Singular Spectrum Analysis, normalized, separated into 2 groups of the target and non-target trial data, and averaged for every 5 trials for each group before classified using a neural network. The purpose of averaging every five target and non-target trials was to emerge the P300 component of even-related potentials so that the target trials could be differentiated from the non-target trials. Further processing by selecting 1 of every 5 processed non-target trials increased the value of sensitivity by 10.9%, it showed that the number of false negatives of target trials was reduced. The results of the classification gave the maximum accuracy of 92.5%. The average values of sensitivity, specificity, and accuracy were 70.8%, 89,8%, and 84.6% respectively.

Original languageEnglish
Title of host publicationICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages80-84
Number of pages5
ISBN (Electronic)9781509066643
DOIs
Publication statusPublished - 2 Jul 2017
Event2nd International Conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2017 - Okinawa, Japan
Duration: 24 Nov 201726 Nov 2017

Publication series

NameICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences
Volume2018-January

Conference

Conference2nd International Conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2017
Country/TerritoryJapan
CityOkinawa
Period24/11/1726/11/17

Keywords

  • EEG signals
  • P300
  • event-related potential
  • multilayer perceptron network
  • singular spectrum analysis

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