EEG Markers for Cognitive Decline in Elderly Using the Reconstructed Phase Space
Date Issued
2012
Date
2012
Author(s)
Huang, Shih-Fang
Abstract
This study develops new markers of dementia for the elderly based on the all-night EEG of a single channel. First of all, the sleep EEG from electrodes C3-A2, C4-A1, O1-A2 and O2-A1 have been recorded for 7 dementia''s patients and 19 age-matched normal controls. Second, the sleep EEG is transformed into 5 power time series corresponding to the delta, theta, alpha, sigma and beta frequency bands by power spectral density.
Using the Reconstructed Phase Space, then use Average Mutual Information to determine the best delay time of phase space reconstruction and then followed by using false nearest neighbor to determine the best invading dimension of phase space reconstruction ; resulting in the five band power time series derived from 26 aged patients which it represents the level of chaos. Lyapunov exponents has been used in this study to identify dementia patients’ EEG characteristics. Results shown that there is a significant difference in P value (p<0.01) in the Lyapunov exponents calculated from the sleep EEG electrode C3-A2 channel Alpha and Theta band power. By looking at the Lyapunov exponents in the Alpha band power calculated from the sleep EEG electrode C4-A1 channel, comparing the Lyapunov exponents between the two patient groups, dementia patient is relatively low and there is a significant difference in the P value (p<0.05).There is also a significant difference between the two patient groups’ reconstructed trail in Alpha and Theta band power in the sleep EEG electrode C3-A2 channel.
From the above study, these Lyapunov exponents seem to be able to reflect neurophysiological degeneration and thus may serve as a marker to identify dementias. Compared with conventional approach, this method is advantageous because only one channel measurement is required. Based on above markers, the relationships between Lyapunov exponent of certain band pairs and cognitive performance are assessed as well. The results demonstrate that the Lyapunov exponent s are strongly correlated with MMSE scores and the subtests of WMS scores .These results demonstrate our proposed method seems to be able to effectively link to well-documented neuropsychological tests. Thus, it indicates that the proposed Lyapunov exponents possess a superior extension for further research.
Subjects
Dementia
Sleep EEG
Similarity
Reconstructed Phase Space
Cognitive Performance
Lyapunov Exponent
Type
thesis
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