首页> 外文期刊>Clinical neurophysiology >Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy.
【24h】

Analysis of regularity in the EEG background activity of Alzheimer's disease patients with Approximate Entropy.

机译:近似熵分析阿尔茨海默氏病患者脑电图背景活动的规律性。

获取原文
获取原文并翻译 | 示例
           

摘要

OBJECTIVE: The aim of this study was to analyse the regularity of the EEG background activity of Alzheimer's disease (AD) patients to test the hypothesis that the irregularity of the AD patients' EEG is lower than that of age-matched controls. METHODS: We recorded the EEG from 19 scalp electrodes in 10 AD patients and 8 age-matched controls and estimated the Approximate Entropy (ApEn). ApEn is a non-linear statistic that can be used to quantify the irregularity of a time series. Larger values correspond to more complexity or irregularity. A spectral analysis was also performed. RESULTS: ApEn was significantly lower in the AD patients at electrodes P3 and P4 (P < 0.01), indicating a decrease of irregularity. We obtained 70% sensitivity and 100% specificity at P3, and 80% sensitivity and 75% specificity at P4. Results seemed to be complementary to spectral analysis. CONCLUSIONS: The decreased irregularity found in the EEG of AD patients in the parietal region leads us to think that EEG analysis with ApEncould be a useful tool to increase our insight into brain dysfunction in AD. However, caution should be applied due to the small sample size. SIGNIFICANCE: This article represents a first step in demonstrating the feasibility of ApEn for recognition of EEG changes in AD.
机译:目的:本研究的目的是分析阿尔茨海默氏病(AD)患者的EEG背景活性的规律性,以检验AD患者EEG异常性低于年龄匹配的对照者的假设。方法:我们记录了10名AD患者和8名年龄匹配的对照组的19头皮电极的脑电图,并估计了近似熵(ApEn)。 ApEn是一种非线性统计量,可用于量化时间序列的不规则性。较大的值对应于更多的复杂性或不规则性。还进行了光谱分析。结果:AD患者在电极P3和P4处的ApEn明显降低(P <0.01),表明不规则性降低。我们在P3处获得70%的敏感性和100%的特异性,在P4处获得80%的敏感性和75%的特异性。结果似乎是光谱分析的补充。结论:壁区AD患者脑电图的不规则性降低,使我们认为ApEn的脑电图分析可能是增加我们对AD脑功能障碍认识的有用工具。但是,由于样本量小,应谨慎行事。重要性:本文代表了证明ApEn识别AD中EEG变化的可行性的第一步。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号