Study of the MEG background activity in Alzheimer's disease patients with scaling analysis methods.
Alzheimer's disease (AD) is one of the most prominent neurodegenerative disorders. The aim of this research work is to study the magnetoencephalogram (MEG) background activity in AD patients using two scaling analysis methods: detrended fluctuation analysis (DFA) and backward detrended moving average (BDMA). Both measures have been designed to quantify correlations in noisy and non-stationary signals. Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 15 patients with probable AD and 15 control subjects. Both DFA and BDMA exhibited two scaling regions with different slopes. Significant differences between both groups were found in the second region of DFA and in the first region of BDMA (p < 0.01, Student's t-test). Using receiver operating characteristic curves, accuracies of 83.33% with DFA and of 80% with BDMA were reached. Our findings show the usefulness of these scaling analysis methods to increase our insight into AD.
Gomez
Carlos
C
Biomedical Engineering Group at Department of Signal Theory and Communications, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Campus Miguel Delibes, 47011 - Valladolid, Spain. cargom@tel.uva.es
Hornero
Roberto
R
Abasolo
Daniel
D
Fernandez
Alberto
A
Poza
Jesus
J
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000544:Alzheimer Disease / Q000503:physiopathology*; D001185:Artificial Intelligence; D005260:Female; D006801:Humans; D015225:Magnetoencephalography / Q000295:instrumentation* / Q000379:methods; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods; D012372:ROC Curve; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted