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新生儿睡眠期的脑电非线性分析方法

Nonlinear Analysis of Electroencephalogram for Neonates in Sleep
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摘要 目的脑电(electroencephalogram,EEG)是新生儿脑功能监护中重要的生理信号,近年研究发现基于非线性动力学的复杂度分析能够客观反映大脑成熟度、睡眠周期和惊厥状态等。方法本文针对神经系统发育正常的早产新生儿组和足月新生儿组,采用近似熵(approximate entropy,ApEn)和样本熵(sample entropy,SampEn)两种非线性参数,对新生儿在安静睡眠期(quiet sleep,QS)和活动睡眠期(active sleep,AS)的脑电信号进行分析。结果神经系统发育正常的新生儿中,AS期的ApEn和SampEn均高于QS期,且具有显著性差异;随着受孕后年龄(postmenstrual age,PMA)的增大,新生儿QS期的ApEn和SampEn的值均随之增加,且波动逐渐减弱,而AS期的ApEn和SampEn的值并无显著变化;绝大多数新生儿在AS期与QS期的SampEn之差高于ApEn之差。结论 AS期新生儿EEG的复杂度大于QS期的复杂度;随着PMA的增大,新生儿EEG的复杂度提高,脑功能发育趋于成熟;ApEn与SampEn在表现新生儿脑电信号复杂度上趋势一致,但SampEn在区分AS与QS方面更具优势。 Objective Electroencephalogram (EEG) is an important physiological signal in neonatal cerebral function monitoring. It is reported that the complexity analysis of neonatal EEG based on nonlinear dynamics can reflect the brain maturity, sleep cycles and convulsions. Methods To investigate the relationship between sleep cycle and nonlinear parameters of neonatal EEG, the EEGs of preterm and full-term neonates were analyzed through approximate entropy (ApEn) and sample entropy (SampEn) in this paper. Results Three phenomena were observed in the neonates with normally developed nervous systems. The first was that the EEG entropies of neonates are higher in active sleep (AS) than those in quiet sleep (QS) with significant differences. The second was that both of ApEns and SampEns of the neonatal EEG increased continuously andfluctuated decreasingly in Qs, changed insignificantly in AS with the rising of the promenstral age (PMA). The third was that the differences of SampEns between AS and QS were more obvious than those of ApEns in most cases. Conclusions The complexity of neonatal EEGs in AS is higher than that in QS, the complexity of neonatal EEGs increases with the rise of their PMA, indicating the gradual maturation of neonatal sleep cycle. The SampEn isin accordance with ApEn in representing the complexity of neonatal EEGs, however more significant in distinguishing between AS and QS.
出处 《北京生物医学工程》 2011年第6期562-566,647,共6页 Beijing Biomedical Engineering
基金 清华大学深圳研究生院种子基金(ZJ20090004) 清华-裕元医学科学研究基金(20200588)资助
关键词 新生儿脑电 近似熵 样本熵 非线性分析 neonatal electroencephalogram approximate entropy sample entropy nonlinear analysis
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参考文献12

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