中国组织工程研究

中国组织工程研究 ›› 2012, Vol. 16 ›› Issue (48): 9114-9120.doi: 10.3969/j.issn.2095-4344.2012.48.035

• 骨与关节临床实践 clinical practice of the bone and joint • 上一篇    

基于局部场电位样本熵分析的麻醉深度监测

师 黎，魏贯军，李晓媛，王治忠，史慧革   

  1. 郑州大学电气工程学院，河南省郑州市 450001
  • 收稿日期:2012-04-05 修回日期:2012-04-26 出版日期:2012-11-25 发布日期:2012-11-25
  • 通讯作者: 魏贯军，硕士，郑州大学电气工程学院，河南省郑州市 450001 wgj_active@ 163.com
  • 作者简介:师黎☆，女，1964年生，河南省尉氏县人，2007年上海大学毕业，博士，博士生导师，教授，主要从事智能检测与生物信号处理与分析的研究。 shili@zzu.edu.cn

Anesthesia depth monitoring based on sample entropy of local field potentials

Shi Li, Wei Guan-jun, Li Xiao-yuan, Wang Zhi-zhong, Shi Hui-ge   

  1. School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, Henan Province, China
  • Received:2012-04-05 Revised:2012-04-26 Online:2012-11-25 Published:2012-11-25
  • Contact: Wei Guan-jun, Master, School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, Henan Province, China wgj_active@163.com
  • About author:Wei Guan-jun, Master, School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, Henan Province, China wgj_active@163.com

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631

被引次数

8

摘要：

背景：目前的麻醉深度监测多以大脑皮质脑电信号分析为主，然而，大脑皮质脑电信号不能反映皮质下组织的功能状况、不包含高频信息并且易受外界环境干扰，从而导致基于大脑皮质脑电信号分析的麻醉深度监测在稳定性、精确性等方面有固有缺陷。
目的：分析局部场电位信号样本熵在麻醉深度监测中的效果，实现麻醉深度的实时监测。
方法：以大鼠为模型动物进行实验，对整个麻醉过程中的大鼠初级视觉皮质局部场电位信号进行快速样本熵计算，并对样本熵曲线动态变化进行分析，判定麻醉状态；然后将样本熵分别与大鼠尾部受热刺激时的甩尾延迟时间、局部场电位信号的中心频率和边缘频率做统计分析，验证基于局部场电位快速样本熵分析的麻醉状态判定方法。
结果与结论：局部场电位信号的样本熵可以快速、准确、稳定地反映大鼠的麻醉深度，用于麻醉深度实时监测。

关键词: 麻醉深度, 样本熵, 局部场电位, 中心频率, 边缘频率

Abstract:

BACKGROUND: Currently, the anesthesia depth monitoring is mostly based on the analysis of electroencephalogram of cerebral cortex, however, the electroencephalogram of cerebral cortex cannot reflect the functional status of the subcortical organization and do not contain high frequency information, meanwhile it is susceptible to external environment interference. For these reasons, anesthesia depth monitoring based on the electroencephalogram has inherent defects in stability and accuracy.
OBJECTIVE: To analyze the effect of sample entropy of the local field potentials in the anesthesia depth monitoring and to realize real-time anesthesia depth monitoring.
METHODS: Firstly, rats were chosen as the model animals. The sample entropy of the local field potentials of the rat's primary visual cortex was calculated during the whole anesthesia process and the dynamic changes of the sample entropy curve were analyzed to determine the anesthesia states. Secondly, the sample entropy of the local field potentials was statistically compared with the time lengths of the rat's tail-flick latency to thermal stimulation, as well as the local field potentials median frequencies and spectral edge frequencies respectively. The correlative analysis was performed according to median frequencies and spectral edge frequencies, and then the validity of the method presented in this paper for judging the anesthesia state was verified.
RESULTS AND CONCLUSION: The results showed that the sample entropy of the local field potentials rapidly, accurately and stably reflects the depth of anesthesia, and constantly monitors the depth of anesthesia.

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