基于脑电近似熵分析的麻醉深度监测研究  

Monitoring of Anesthesia Depth Based on Approximate Entropy of EEG.

作　　者：徐进[1] 郑崇勋[1] 和卫星[1] 

机构地区：[1]西安交大生物医学工程信息工程教育部重点实验室,生物医学工程研究所,陕西西安710049

出　　处：《航天医学与医学工程》2004年第3期205-209,共5页Space Medicine & Medical Engineering

基　　金：国家自然科学基金 (NO .3 0 170 2 5 7) ;西安交大校基金 (No .5 73 0 0 6)资助

摘　　要：目的通过对麻醉状态下脑电 (EEG)的近似熵 (ApEn)分析 ,寻找适用于临床手术的麻醉深度实时监测参数。方法对SD大鼠在不同麻醉深度下提取的脑电 (EEG)信号进行近似熵分析。结果EEG的近似熵随麻醉深度的加深而减少 ,反之亦然。文中还对近似熵与Lempel Ziv复杂度C(n)在麻醉深度监测上的效果进行了对比分析。结论近似熵算法简单、计算所需数据序列短、抗干扰强 ,因此对脑电信号进行近似熵动态分析为临床麻醉深度监测提供了一个新的方法。Objective To find a useful index for real-time monitoring of depth of anesthesia by analysing Approximate Entropy (ApEn) of Electroencephalogram (EEG). Method The ApEn of EEG of SD rats corresponding to different depth of anesthesia was studied and the relationship between ApEn and the depth of anesthesia was analysed. Result The results showed that the ApEn of EEG will decrease while the depth of anesthesia increases and vice versa. Comparison between ApEn and Lempel-Ziv complexity response to depth of anesthesia was also made.Conclusion ApEn can detect the depth of anesthesia sensitively. The algorithm of ApEn can be used for short time series and is highly resistant to short strong transient interference, so it may be used as a practical index for real-time monitoring of the depth of anesthesia in clinical practice.

关 键 词：麻醉 深度 近似熵 脑电图 复杂度 

分 类 号：R318.6[医药卫生—生物医学工程]