Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer's Disease
Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer's Disease
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DOI：
10.1155/2018/8915079
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发表时间：
2018-01-01
期刊：
影响因子：
2.3
通讯作者：
Ifeachor, Emmanuel
中科院分区：
文献类型：
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作者：
Al-Nuaimi, Ali H. Husseen;Jammeh, Emmanuel;Ifeachor, Emmanuel
阿尔茨海默病（AD）是一种影响认知脑功能的进行性疾病，并且在其临床表现之前多年开始。一种生物标志物，提供了一个定量测量的变化，在大脑中由于AD在早期阶段将是有用的早期诊断AD，但这将涉及处理大量的人，因为高达50%的痴呆症患者没有得到正式的诊断。因此，需要准确、低成本且易于使用的生物标志物，其可用于在早期阶段检测AD。基于脑电图（EEG）的生物标志物可能在AD的早期诊断中发挥重要作用，因为它们可以满足这些需求。这是一项横断面研究，旨在证明EEG复杂性测量在早期AD诊断中的有用性。我们重点讨论了在AD检测中表现出最大希望的三种复杂性方法，Tsallis熵（TsEn），Higuchi分形维数（HFD）和Lempel-Ziv复杂性（LZC）方法。与以前的方法不同，在这项研究中，复杂性的措施是来自EEG频带（而不是整个EEG），因为EEG活动与AD有显着的关联，这导致了增强的性能。结果表明，AD患者具有显着较低的TsEn，HFD，和LZC值为特定的EEG频带和特定的EEG通道，该信息可用于检测AD的灵敏度和特异性超过90%。
Alzheimer's disease (AD) is a progressive disorder that affects cognitive brain functions and starts many years before its clinical manifestations. A biomarker that provides a quantitative measure of changes in the brain due to AD in the early stages would be useful for early diagnosis of AD, but this would involve dealing with large numbers of people because up to 50% of dementia sufferers do not receive formal diagnosis. Thus, there is a need for accurate, low-cost, and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, electroencephalogram (EEG) based biomarkers can play a vital role in early diagnosis of AD as they can fulfill these needs. This is a cross-sectional study that aims to demonstrate the usefulness of EEG complexity measures in early AD diagnosis. We have focused on the three complexity methods which have shown the greatest promise in the detection of AD, Tsallis entropy (TsEn), Higuchi Fractal Dimension (HFD), and Lempel-Ziv complexity (LZC) methods. Unlike previous approaches, in this study, the complexity measures are derived from EEG frequency bands (instead of the entire EEG) as EEG activities have significant association with AD and this has led to enhanced performance. The results show that AD patients have significantly lower TsEn, HFD, and LZC values for specific EEG frequency bands and for specific EEG channels and that this information can be used to detect AD with a sensitivity and specificity of more than 90%.