EEG的信息熵分析

INFORMATION ENTROPY ANALYSIS OF EEG

用非线性动力学观点来分析EFG认为它可能是一个不稳定混沌态,并提出了用信息熵的方法来分析这一混沌态的结构特征.临床观察发现在不同功能态下其特征是不一样的,并发现精神病人中信息传递特征参数有“倒置”现象,这对EEG分析和临床脑电诊断都是有很大意义的.

Human EEG is an unstable chaotic state in view of nonlinear dynamics analysis. In this paper an information entropy measurement to characterize the EEG temporal series is introduced. The information entropy was computed and showed to be closely related to the brain functional states. It was also found that the characteristic parameters of EEG of some mental patients were inverted as that of normal person. It is very helpful and important to diagnose Psychiatric patients.