Analysis of EEG Time Series Recorded from Alzheimer Patients Based on Their Spectral Content
In this paper, EEG recordings on each channel are seen as non stationary time series. We assume a piecewise stationary model for the signal where the changes affect the power spectrum. Such a model is particularly relevant for analyzing Alzheimer disease (AD) dataset as the disease leads to variation of the frequency rhythms. Our method is devoted to the estimation of the partition. We define a criterion based on a regularized periodogram to estimate the spectrum and on the power spectrum on predefined frequency bands to estimate the change points. The method produces new markers designed to be used for the discrimination between control and AD patients.
Aurelien Hazart Francois-Benoit Vialatte Andrzej Cichocki
Laboratory for Advanced Brain Signal Processing, Riken Brain Science Institute, Wakoshi, Saitama, Japan
国际会议
The Second International Conference on Cognitive Neurodynamics--2009(第二届国际认知神经动力学会议)
杭州
英文
717-722
2009-11-15（万方平台首次上网日期，不代表论文的发表时间）