發(fā)布時間：2018-07-02 08:17

  本文選題：睡眠分期 + 樣本熵��； 參考：《江蘇大學學報(自然科學版)》2009年05期

【摘要】：運用樣本熵從波士頓Beth Israel睡眠腦電實驗數(shù)據(jù)中提取睡眠特征值,對睡眠分期進行研究.針對腦電屬于微弱非平穩(wěn)隨機信號、難于提取特征的特點,利用小波變換先有效地消除腦電信號中的噪聲,再計算其樣本熵用以表征睡眠各分期.計算結果表明,由清醒期到非快速眼動的Ⅳ期過程中,其樣本熵值呈規(guī)律性逐漸變小,與該庫中專家評定的結果相符.這說明經(jīng)過小波消噪和樣本熵處理的腦電信號能準確地反映睡眠各期的變化特征,比用近似熵表征睡眠分期更準確、運算速度更快,完全適用于非平穩(wěn)隨機信號的處理.
[Abstract]:The sleep stages were studied by extracting the sleep characteristic values from the data of Beth Israel sleep EEG experiment in Boston using sample entropy. Because EEG is a weak non-stationary random signal, it is difficult to extract features. Wavelet transform is used to effectively eliminate the noise in EEG signal, and then the sample entropy is calculated to characterize the sleep stages. The calculated results show that the entropy values of the samples decrease gradually during the period 鈪，

本文編號：2089500