- 學位論文
以相空間重構法建立長者認知退化腦波特徵
EEG Markers for Cognitive Decline in Elderly Using the Reconstructed Phase Space
摘要
本研究之目的在利用混沌理論分析高齡者睡眠腦波訊號，以建立辨識失智症長者的特徵指標。本研究對19位認知功能正常與7位失智症長者進行睡眠檢查，記錄其C3-A2、C4-A1、O1-A2、O2-A1腦電位之腦波，以功率頻譜密度法將腦波分成Delta、Theta、Alpha、Sigma、Beta 5條能量時間序列，並運用混沌理論的相空間重構法分析該五條訊號，以平均互訊息法決定相空間最佳時間延遲量，以假鄰近點比例法決定相空間最佳的重建維度，以建立26位長者重構相空間後的5條能量時間序列；接著計算可以刻畫相空間整體軌跡發散率的李亞普諾指數，以定出各時間序列的混沌程度，最後再比較正常與失智症長者的李亞普諾指數。 結果發現，正常及失智症長者C3-A2腦電位的Alpha及Theta頻帶能量時間序列，經相空間重構所計算出來的李亞普諾指數具有顯著的差異(p<0.01)。C4-A1腦電位所計算出來的李亞普諾指數，失智症患者在Alpha頻帶的李亞普諾指數也相對較低，且與正常長者有顯著差異(p<0.05)。此外，重建這兩群長者C3-A2腦電位的Alpha和Theta頻帶在相空間中的軌跡，也發現兩群受試者具有明顯的差異。 本研究亦將李亞普諾指數與臨床認知表現作一統計分析，結果顯示C3-A2腦電位Alpha及Theta頻帶的李亞普諾指數與診斷失智症之量表MMSE具有高度的相關性。此外，C3-A2腦電位Alpha及Theta頻帶的李亞普諾指數也能有效連結到一些臨床相關的認知測驗。 研究結果顯示，Alpha和Theta頻帶能量時間序列以相空間重構法分析後所得到的李亞普諾指數，可反映出神經生理與認知的退化，並且可以作為辨識失智症長者的特徵。與傳統的10-20系統腦波量測相較，本研究所提出之失智症長者特徵指標只要單一頻道睡眠腦波量測即可進行失智症的辨識，可望成為辨識失智症的有利工具。
並列摘要
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.
參考文獻
延伸閱讀
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