Analysis of MEG recordings from Alzheimer's disease patients with sample and multiscale entropies

Carlos Gomez*, Roberto Hornero, Daniel Abasolo, Alberto Fernandez, Javier Escudero

*Corresponding author for this work

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

Abstract

Alzheimer's disease (AD) is one of the most prominent neurodegenerative disorders. The aim of this study is to analyze the magnetoencephalogram (MEG) background activity in AD patients using sample entropy (SampEn) and multiscale entropy (MSE). The former quantifies the signal regularity, while the latter is a complexity measure. These concepts, irregularity and complexity, are linked although the relationship is not straightforward. Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 20 patients with probable AD and 21 control subjects. Our results show that MEG recordings are less complex and more regular in AD patients than in control subjects. Significant differences between both groups were found in some MEG channels with both methods (P <0.01, Student's t-test with Bonferroni's correction). Using receiver operating characteristic curves, accuracies of 75.6% with SampEn and of 87.8% with MSE were reached. Our findings show the usefulness of these entropy measures to increase our insight into AD.

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)
Pages6184-6187
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
CountryFrance
CityLyon
Period22/08/0726/08/07

Keywords

  • EEG BACKGROUND ACTIVITY
  • COMPLEXITY

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