Magnetoencephalogram blind source separation and component selection procedure to improve the diagnosis of Alzheimer's disease patients

Javier Escudero*, Roberto Hornero, Daniel Abasolo, Alberto Fernandez, Jesus Poza

*Corresponding author for this work

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

Abstract

The aim of this study was to improve the diagnosis of Alzheimer's disease (AD) patients applying a blind source separation (BSS) and component selection procedure to their magnetoencephalogram (MEG) recordings. MEGs from 18 AD patients and 18 control subjects were decomposed with the algorithm for multiple unknown signals extraction. MEG channels and components were characterized by their mean frequency, spectral entropy, approximate entropy, and Lempel-Ziv complexity. Using Student's t-test, the components which accounted for the most significant differences between groups were selected. Then, these relevant components were used to partially reconstruct the MEG channels. By means of a linear discriminant analysis, we found that the BSS-preprocessed MEGs classified the subjects with an accuracy of 80.6%, whereas 72.2% accuracy was obtained without the BSS and component selection procedure.

Original languageEnglish
Title of host publication2007 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-16
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages5437-5440
Number of pages4
ISBN (Print)978-1-4244-0787-3
Publication statusPublished - 2007
Event29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Lyon, France
Duration: 22 Aug 200726 Aug 2007

Publication series

NamePROCEEDINGS OF ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY
PublisherIEEE
ISSN (Print)1094-687X

Conference

Conference29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/TerritoryFrance
CityLyon
Period22/08/0726/08/07

Keywords

  • APPROXIMATE ENTROPY
  • BACKGROUND ACTIVITY
  • COMPLEXITY
  • DYNAMICS

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