Dimension reduction of RCE signal by PCA and LPP for estimation of the sleeping

Yohei Tomita, Yasue Mitsukura, Toshihisa Tanaka, Jianting Cao

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

Abstract

Irregular hour and suffering from stress cause driver doze and falling asleep during important situations. Therefore, it is necessary to know the mechanism of the sleeping. In this study, we distinct the sleep conditions by the rhythmic component extraction (RCE). By using this method, a particular EEG component is extracted as the weighted sum of multi-channel signals. This component concentrates the energy in a certain frequency range. Furthermore, when the weight of a specific channel is high, this channel is thought to be significant for extracting a focused frequency range. Therefore, the sleep conditions are analyzed by the power and the weight of RCE. As for weight analysis, the principal component analysis (PCA) and the locality preserving projection (LPP) are used to reduce the dimension. In the experiment, we measure the EEG in two conditions (before and during the sleeping). Comparing these EEGs by the RCE, the power of the alpha wave component decreased during the sleeping and the theta power increased. The weight distributions under two conditions did not significantly differ. It is to be solved in the further study.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011
Pages306-312
Number of pages7
EditionPART 3
DOIs
Publication statusPublished - 2011 Jun 6
Event8th International Symposium on Neural Networks, ISNN 2011 - Guilin, China
Duration: 2011 May 292011 Jun 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume6677 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Symposium on Neural Networks, ISNN 2011
CountryChina
CityGuilin
Period11/5/2911/6/1

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Keywords

  • EEG
  • LPP
  • PCA
  • RCE

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Tomita, Y., Mitsukura, Y., Tanaka, T., & Cao, J. (2011). Dimension reduction of RCE signal by PCA and LPP for estimation of the sleeping. In Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011 (PART 3 ed., pp. 306-312). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6677 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-21111-9_34