Electroencephalogram Background Activity Characterization with Detrended Moving Average in Alzheimer's Disease Patients

Daniel Abasolo*, Roberto Hornero, Carlos Gomez, Javier Escudero, Pedro Espino

*Corresponding author for this work

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

Abstract / Description of output

The aim of this study was to analyse the electroencephalogram (EEG) background activity in Alzheimer's disease (AD) with the Detrended Moving Average (DMA) method, a new approach to quantify correlation properties in non-stationary signals with underlying trends. EEGs were recorded from the 19 scalp loci of the international 10-20 system in 11 AD patients and 11 age-matched controls. Our results showed two scaling regions in all subjects' channels, with a clear bend when their corresponding slopes (alpha(1) and alpha(2)) were distinctly different. With the exception of electrode T4, the alpha(1) values were lower in control subjects than in AD patients, with significant differences at TS, P3, P4 and O1 (p <0.01, Student's t-test). On the other hand, alpha(2) values were higher in control subjects than in AD patients, with significant differences only at F4. Furthermore, we evaluated the ability of alpha(2) to discriminate AD patients from control subjects at these electrodes using ROC plots. We obtained a maximum accuracy of 81.82% at O1 with alpha(1) and at F4 with alpha(2). These findings suggest that the scaling behaviour of the EEG is sensitive to AD and that the DMA method could help to increase our insight into brain dysfunction in AD.

Original languageEnglish
Title of host publicationWISP 2009: 6TH IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING, PROCEEDINGS
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers
Pages211-215
Number of pages5
ISBN (Print)978-1-4244-5058-9
Publication statusPublished - 2009
Event6th IEEE International Symposium on Intelligent Signal Processing - Budapest, Hungary
Duration: 26 Aug 200928 Aug 2009

Publication series

NameInternational Symposium on Intelligent Signal Processing-WISP
PublisherIEEE

Conference

Conference6th IEEE International Symposium on Intelligent Signal Processing
Country/TerritoryHungary
Period26/08/0928/08/09

Keywords / Materials (for Non-textual outputs)

  • RANGE TEMPORAL CORRELATIONS
  • EEG
  • OSCILLATIONS
  • ENTROPY

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