Application of approximate entropy and complexity analysis in monitoring depth of anesthesia
- VernacularTitle:近似熵和复杂度分析在麻醉深度监测中的应用
- Author:
Dongyu WU
;
Gui CAI
;
Ling YING
- Publication Type:Journal Article
- Keywords:
electroencephalography;
nonlinear dynamics;
anesthesia;
consciousness
- From:
Medical Journal of Chinese People's Liberation Army
2001;0(12):-
- CountryChina
- Language:Chinese
-
Abstract:
Objective The present study was undertaken to investigate the properties of nonlinear dynamics of EEG and the changes in depth of anesthesia with real-time approximate entropy (ApEn) and complexity (Cx) nonlinear indexes monitoring during anesthesia. Methods EEG was recorded in 65 in-patients. They were randomly divided into 4 groups: isoflurane, sevoflurane, desflurane (n=15, respectively), and propofol intravenous anesthesia (n=20) groups. The EEG derived parameters ApEn and Cx non-linear indexes were calculated simultaneously during the whole operation including rest state with eyes closed, anesthetic induction, intraoperation, recovery, post-operation awaking. Results ApEn and Cx nonlinear indexes remained the highest during rest state. Both of them kept decreasing during anesthetic induction. They dropped to a relative lower value and leveled off in the intra-operation period. Both of them rose gradually during recovery period and returned to a high level in the post-operation awaking period (correspondingly, ApEn: 0.87, 0.78, 0.55, 0.64 and 0.83. Cx: 0.58, 0.54, 0.38, 0.46 and 0.57). Conclusions With ApEn and Cx non-linear indexes, changes in depth of anesthesia from EEG signal could be real-timely monitored and precisely measured. Nonlinear dynamic analysis might provide us with more information about consciousness and cognition during general anesthesia.
