PDF(Pubmed)
Abstract：
Stroke is a cerebrovascular illness that brings about the demise of brain tissue. It is the third most prevalent cause of mortality worldwide and a significant contributor to physical impairment. Generally, stroke is triggered by blood clots obstructing the brain\'s blood vessels, or when these vessels rupture. And, the cognitive impairment\'s evaluation and detection after stroke is crucial research issue and significant project. Thus, the objective of this work is to explore an potential neuroimage tool and find their EEG biomarkers to evaluate and detect four cognitive impairment levels after stroke. In this study, power density spectrum (PSD), functional connectivity map, and one-way ANOVA methods were proposed to analyze the EEG biomarker differences, and the number of patient participants were thirty-two human including eight healthy control, mild, moderate, severe cognitive impairment levels, respectively. Finally, healthy control has significant PSD differences compared to mid, moderate and server cognitive impairment groups. And, the theta and alpha bands of severe cognitive impairment groups have presented consistent superior PSD power at the right frontal cortex, and the theta and beta bands of mild, moderated cognitive impairment (MoCI) groups have shown significant similar superior PSD power tendency at the parietal cortex. The significant gamma PSD power difference has presented at the left-frontal cortex in the mild cognitive impairment (MCI) groups, and severe cognitive impairment (SeCI) group has shown the significant PSD power at the gamma band of parietal cortex. At the point of functional connectivity map, the SeCI group appears to have stronger functional connectivity compared to the other groups. In conclusion, EEG biomarkers can be applied to classify different cognitive impairment groups after stroke. These findings provide a new approach for early detection and diagnosis of cognitive impairment after stroke and also for the development of new treatment options.
摘要：
中风是导致脑组织死亡的脑血管疾病。它是全球第三大最普遍的死亡原因，也是造成身体损害的重要原因。一般来说,中风是由血液凝块阻塞大脑的血管引发的，或者当这些血管破裂时。And,卒中后认知损害的评估和检测是至关重要的研究问题和重要课题。因此，这项工作的目的是探索一种潜在的神经影像工具,并找到其脑电图生物标志物,以评估和检测卒中后4种认知障碍水平.在这项研究中,功率密度谱(PSD),功能连接图，并提出了单因素方差分析方法来分析脑电生物标志物的差异，患者人数为32人，包括8名健康对照，温和,中度,严重的认知障碍水平，分别。最后,健康对照与中期相比有显著的PSD差异，中度和服务器认知障碍组。And,严重认知障碍组的theta和alpha谱带在右额叶皮层表现出一致的优越PSD能力，温和的θ和β带，中度认知障碍（MoCI）组在顶叶皮层显示出明显相似的PSD功能倾向。在轻度认知障碍（MCI）组中，左额叶皮层出现了显着的伽玛PSD功率差异，严重认知障碍（SeCI）组在顶叶皮层的伽马波段显示出明显的PSD能力。在功能连接图的点上，与其他组相比，SeCI组似乎具有更强的功能连通性。总之,脑电图生物标志物可用于脑卒中后不同认知障碍组的分类。这些发现为早期发现和诊断卒中后认知障碍以及开发新的治疗方案提供了新的方法。
