Nonlinear forecasting measurement of magnetoencephalogram recordings from Alzheimer's disease patients
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 14...
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Veröffentlicht in: | 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2008-01, Vol.2008, p.2153-2156 |
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Zusammenfassung: | 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. |
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ISSN: | 1094-687X 1557-170X 1558-4615 |
DOI: | 10.1109/IEMBS.2008.4649620 |