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Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients.

Gómez, C, Hornero, R, Mediavilla, A, Fernández, A and Abásolo, D (2008) Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients.

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Abstract

The goal of this study was to analyze the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD) using a nonlinear forecasting measure. It is a nonparametric method to quantify the predictability of time series. Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 15 patients with probable AD and 15 elderly control subjects. Stationary epochs of 5 seconds (848 points, sample frequency of 169.55 Hz) were selected. Our results showed that AD patients' MEGs were more predictable than controls' recordings. Additionally, an accuracy of 76.7% (80.0% sensitivity; 73.3% specificity) was reached using a receiver operating characteristic curve. These preliminary results suggest the usefulness of nonlinear forecasting to gain a better understanding of dynamical processes underlying the MEG recording.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
AuthorsEmailORCID
Gómez, CUNSPECIFIEDUNSPECIFIED
Hornero, RUNSPECIFIEDUNSPECIFIED
Mediavilla, AUNSPECIFIEDUNSPECIFIED
Fernández, AUNSPECIFIEDUNSPECIFIED
Abásolo, DUNSPECIFIEDUNSPECIFIED
Date : 2008
Identification Number : 10.1109/IEMBS.2008.4649620
Uncontrolled Keywords : Aged, Algorithms, Alzheimer Disease, Diagnosis, Computer-Assisted, Female, Forecasting, Humans, Magnetoencephalography, Male, Middle Aged, Nonlinear Dynamics, Predictive Value of Tests, ROC Curve
Additional Information : © 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 30 Jan 2013 09:27
Last Modified : 23 Sep 2013 19:36
URI: http://epubs.surrey.ac.uk/id/eprint/713805

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