摘要
背景:近似熵是一种描述信号复杂性和规律性的非线性动力学方法,只需较少数据就能度量信号的复杂性。目的:探讨不同思维状态下脑电近似熵的变化规律,以及近似熵在认知过程中的作用。方法:用近似熵对20名健康成年人在安静闭眼、安静睁眼、闭眼记忆、闭眼心算和图片识别5种状态下的脑电数据进行分析。结果与结论:近似熵值在闭眼计算和闭眼记忆思维状态高于安静闭眼状态,在图片识别状态下高于安静睁眼状态(P<0.01);近似熵在安静闭眼和安静睁眼状态下各导联处于较低水平,在闭眼心算和闭眼记忆思维状态下各导联处明显增加。说明不同思维状态和不同导联部位对近似熵均有影响;近似熵在认知作业过程下较安静状态增高,并且不同思维状态下大脑功能活动的复杂性不同。因此脑电近似熵分析适用于认知过程脑功能活动变化规律研究,有助于了解大脑的工作机制。
BACKGROUND：Approximate entropy（ApEn） is a nonlinear dynamics that describes the signal complexity and regularity,and it can measure the complexity of the signal with less data.OBJECTIVE：To investigate the changes of ApEn of electroencephalogram（EEG） under different mental states,and the application of ApEn for cognitive function research.METHODS：EEG was recorded in 20 healthy young volunteers at five stages（eyes closed,eyes opened,recalled with eyes closed,mental arithmetic with eyes closed and pictures identification with eyes opened）.ApEn was calculated for all subjects.RESULTS AND CONCLUSION：ApEn values were higher in calculated and recalled with the eyes closed than eyes closed,and higher in pictures identification than eyes opened（P 0.01）.ApEn displayed a low level in all channels with eyes closed or opened,and was increases with thinking and memory state.In different mental states,the complexity of mental functions was different.ApEn methods are appropriate for the study of cognitive functions and can help understand the working mechanism of brain during mental activities.
出处
《中国组织工程研究与临床康复》
CAS
CSCD
北大核心
2010年第43期8077-8080,共4页
Journal of Clinical Rehabilitative Tissue Engineering Research
基金
重庆市重大科技专项"新型医疗器械"项目的子项目~~
