■考虑到大脑活动涉及复杂网络中数百万个神经元之间的交流,非线性分析是研究脑电图(EEG)的可行工具。这篇综述的主要目的是整理在多发性硬化症(MS)患者的脑电图中利用混沌测量和非线性动力学分析的研究,并讨论混沌理论技术对理解的贡献,诊断,和治疗女士
■使用系统评价和荟萃分析(PRISMA)的首选报告项目,数据库EbscoHost,IEEE,ProQuest,PubMed,科学直接,WebofScience,和GoogleScholar搜索了将混沌理论应用于MS患者脑电图分析的出版物。
■使用VOSviewer软件进行的书目分析关键字共现分析表明,MS是研究的重点,对MS诊断的研究已从常规方法转移,比如磁共振成像,近年来的脑电图技术。本综述共纳入17项研究。在包括的文章中,九项研究检查了静息状态,和八个检查基于任务的条件。
■尽管MS的非线性EEG分析是一个相对新颖的研究领域,研究结果被证明是有益和有效的。最常用的非线性动力学分析是分形维数,复发定量分析,互信息,和连贯性。所选择的每个分析都提供了独特的评估,以实现本审查的目标。在考虑讨论的局限性时,使用MS数据的非线性分析是一条有前途的前进道路。
UNASSIGNED: Considering that brain activity involves communication between millions of neurons in a complex network, nonlinear analysis is a viable tool for studying electroencephalography (EEG). The main objective of this
review was to collate studies that utilized chaotic measures and nonlinear dynamical analysis in EEG of multiple sclerosis (MS) patients and to discuss the contributions of
chaos theory techniques to understanding, diagnosing, and treating MS.
UNASSIGNED: Using the preferred reporting items for systematic reviews and meta-analysis (PRISMA), the databases EbscoHost, IEEE, ProQuest, PubMed, Science Direct, Web of Science, and Google Scholar were searched for publications that applied
chaos theory in EEG analysis of MS patients.
UNASSIGNED: A bibliographic analysis was performed using VOSviewer software keyword co-occurrence analysis indicated that MS was the focus of the research and that research on MS diagnosis has shifted from conventional methods, such as magnetic resonance imaging, to EEG techniques in recent years. A total of 17 studies were included in this
review. Among the included articles, nine studies examined resting-state, and eight examined task-based conditions.
UNASSIGNED: Although nonlinear EEG analysis of MS is a relatively novel area of research, the findings have been demonstrated to be informative and effective. The most frequently used nonlinear dynamics analyses were fractal dimension, recurrence quantification analysis, mutual information, and coherence. Each analysis selected provided a unique assessment to fulfill the objective of this
review. While considering the limitations discussed, there is a promising path forward using nonlinear analyses with MS data.