睡眠EEG的多尺度信息熵分析  

Analysis of Sleep EEG by Using Multi-Scale Entropy

作　　者：宦飞[1] 王志中[1] 郑崇勋[2] 

机构地区：[1]上海交通大学生物医学工程系,200030 [2]西安交通大学生物医学工程研究所,710032

出　　处：《北京生物医学工程》2001年第1期6-8,共3页Beijing Biomedical Engineering

基　　金：国家自然科学基金!资助项目 (No.39970 2 0 4)

摘　　要：本文提出一种基于连续小波变换的睡眠 EEG分析方法。该方法使用 Morlet小波计算 EEG信息的小波变换系数 ,通过计算 EEG信号在多个尺度上小波系数的熵分析睡眠 EEG。结果表明 :浅睡阶段 EEG信号的多尺度熵的变化模式与深睡阶段的多尺度熵的变化模式不同 ,REM睡眠期间 EEG信号的多尺度熵的变化与深睡阶段类似 ,使用多尺度熵可以区分 REM睡眠和浅睡时 EEG之间的差别。Based on application of continuous wavelet transform, a new method for analyzing sleep EEG is presented. The wavelet transform coefficients of the EEG signals are computed by using Morlet's wavelet. The information content carried by the wavelet coefficients on any scale is measured with entropy. Analyzing sleep EEG, it may be observed that the change in the multi-scale entropy of the EEG signals in light sleep stage is different from that in deep sleep stage, and the change in the multi-scale entropy of the EEG signals in REM sleep stage is similar to that in deep sleep. By this method, we can distinguish the characteristics of the EEG in light sleep stage and that in the REM sleep stage.

关 键 词：脑电图 睡眠 小波分析 熵 多尺度信息熵 

分 类 号：R741.044[医药卫生—神经病学与精神病学]