基于脑电格子复杂性分析的麻醉深度监测研究

Monitoring Anesthetic Depth Based on Lattice Complexity of Electroencephalogram

基于符号序列的细粒化方法和两种分划方法(均值分划与排列分划),将格子复杂性(Lattice complexity,LC)用于麻醉时期脑电信号复杂度分析。选取了30例丙泊酚全麻患者,分别计算了LC和lempel-ziv(LZ)复杂性,并比较了两者与BIS的Pearson相关性。结果表明诱导期均值分划LC效果较好,恢复期排列分划LC效果较好,与BIS的Pearson相关性为0.963 6。对于整个麻醉期均值分划LC效果最佳,与BIS相关性为0.841 6,同时细粒化指数一般取3可得到不错的效果,可为临床麻醉深度监测提供一个新方法。

Based on fine-graining method and two partition methods（permutation partition and average partition）,lattice complexity（LC）was used in EEG complexity analysis under anesthesia in this paper.By using the EEG of 40 patients who underwent general anesthesia with propofol,we calculated the Lattice complexity and lempel-ziv（LZ）complexity and compared Pearson＇s correlation coefficient between LC,LZ and BIS values. Results showed that duringanesthesia induction period,average partition with lattice complexity get better effect. While during anesthesiarecovery period,permutation partition with lattice complexity get better result,and the Pearson＇s correlation coeffi-cient between LC and BIS values was 0.963 6. During the whole anesthesia period,Average partition with lattice com-plexity get better effect,and the the Pearson＇s correlation coefficient between LC and BIS values was 0.841 6. Thefine-graining order take 3 can get good result. All these provide a new method for clinical anesthetic depth monitoring.