Document Detail


MEG analysis in Alzheimer's disease computing approximate entropy for different frequency bands.
MedLine Citation:
PMID:  21096583     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
The goal of this study was to analyze the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD) using a regularity measure: approximate entropy (ApEn). This measure was computed for a broad band (0.5-40 Hz) as well as typical frequency bands (delta, theta, alpha, beta and gamma). Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 15 patients with probable AD and 15 elderly control subjects. Our results showed that AD patients' MEGs were more regular than controls' recordings at all frequency bands, with the exception of beta. Additionally, there were statistically significant differences (p 〈 0.01, Student's t-test) at the broad and delta bands. Using receiver operating characteristic curves, the highest accuracy (83.33%) was reached at delta band. These results suggest the usefulness of ApEn to gain a better understanding of dynamical processes underlying the MEG recording.
Authors:
Carlos Gomez; Daniel Abasolo; Jesus Poza; Alberto Fernandez; Roberto Hornero
Related Documents :
11538323 - Band structure of the solar system: an objective test of the grouping of planets and s...
20329843 - On the significance of phase in the short term fourier spectrum for speech intelligibil...
12673243 - Egg recognition and counting reduce costs of avian conspecific brood parasitism.
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference     Volume:  1     ISSN:  1557-170X     ISO Abbreviation:  Conf Proc IEEE Eng Med Biol Soc     Publication Date:  2010  
Date Detail:
Created Date:  2010-11-24     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101243413     Medline TA:  Conf Proc IEEE Eng Med Biol Soc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2379-82     Citation Subset:  IM    
Affiliation:
Biomedical Engineering Group at Department of Signal Theory and Communications, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Campus Miguel Delibes, 47011, Spain.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Nonlinear, multiple-input modeling of cerebral autoregulation using Volterra Kernel estimation.
Next Document:  Characterization of activity epochs in actimetric registries for infantile colic diagnosis: Identifi...