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.