A design of the EEG feature detection and condition classification

Junko Murakami, Shin Ichi Ito, Yasue Mitsukura, Jianting Cao, Minoru Fukumi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we classify the human conditions (before and after meal, before and after smoking) and extract the frequency feature of conditions by using the electroencephalograms (EEG). First, we measure the EEG data. Then, we classify the conditions by using the principal component analysis (PCA). Moreover, the EEG data is reconstructed by using the questionnaires and the result of classification. From the result, we consider ideal circumstance for the EEG measurement. Finally, the EEG data is decompressed to consider the EEG features of conditions. Then, in order to show the effectiveness of the proposed method, computer simulations are done.

Original languageEnglish
Title of host publicationSICE Annual Conference, SICE 2007
PublisherSociety of Instrument and Control Engineers (SICE)
Pages2798-2803
Number of pages6
ISBN (Print)4907764286, 9784907764289
DOIs
Publication statusPublished - 2007 Jan 1
EventSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007 - Takamatsu, Japan
Duration: 2007 Sep 172007 Sep 20

Publication series

NameProceedings of the SICE Annual Conference

Other

OtherSICE(Society of Instrument and Control Engineers)Annual Conference, SICE 2007
CountryJapan
CityTakamatsu
Period07/9/1707/9/20

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Keywords

  • Condition
  • EEG
  • PCA

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Murakami, J., Ito, S. I., Mitsukura, Y., Cao, J., & Fukumi, M. (2007). A design of the EEG feature detection and condition classification. In SICE Annual Conference, SICE 2007 (pp. 2798-2803). [4421464] (Proceedings of the SICE Annual Conference). Society of Instrument and Control Engineers (SICE). https://doi.org/10.1109/SICE.2007.4421464