北京生物醫(yī)學(xué)工程

腦電信號(hào)的多重分形去趨勢波動(dòng)分析__________________

Multifractaldetrended fluctuation analysis on electroencephalography

作者：鄒鳴高庸王新猛王琪鄭婕莊建軍黃曉林

單位：                      南京森林警察學(xué)院偵查系(南京210046)        

關(guān)鍵詞：腦電信號(hào)；多重分形；奇異譜；Hurst指數(shù)

分類號(hào)：

出版年·卷·期（頁碼）：2013·32·3（226-229）

摘要：

目的利用一種多重分形去趨勢波動(dòng)分析方法探索腦電信號(hào)的波動(dòng)和不規(guī)則信息中隱藏的規(guī)律。方法數(shù)據(jù)來源于德國波恩大學(xué)醫(yī)學(xué)中心的數(shù)據(jù)庫，分別對睜眼、閉眼、正常人、癲癇未發(fā)作期和發(fā)作期患者的腦電信號(hào)進(jìn)行計(jì)算，求出各自的奇異譜寬度Δα和Hurst指數(shù)，并對各組數(shù)據(jù)的均值和方差做統(tǒng)計(jì)分析。結(jié)果奇異譜寬度Δα可以有效區(qū)分不同的腦電狀態(tài)。結(jié)論腦電信號(hào)的多重分形去趨勢波動(dòng)分析方法有助于癲癇疾病的早期診斷。

Objective To explore the significant information deeply hidden in the irregular electroencephalography (EEG) signals with multifractaldetrended fluctuation analysis. Methods Multifractal singular spectrum and Hurst index of EEG signals in different groups were calculated based on the data from the database in Medical Center of University of Bonn. Results Multifractal singular spectrum discriminated different states of EEG effectively. Conclusions Multifractaldetrended fluctuation analysis is helpful to make an early diagnosis for epilepsy.

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