Uudeberg Tuuli, Paeske Laura, Hinrikus Hiie, Lass Jaanus, Bachmann Maie
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:276-279. doi: 10.1109/EMBC44109.2020.9175274.
The aim of this study was to evaluate individual level of natural variability of electroencephalogram (EEG) based markers. Three linear: alpha power variability, spectral asymmetry index, relative gamma power and three nonlinear methods: Higuchi's fractal dimension, detrended fluctuation analysis, and Lempel-Ziv complexity were selected. The markers were evaluated over 15 sessions acquired in 14 months. The results indicate that individual natural variability for five of the selected markers is lower compared to differences between healthy and depressed groups of subjects in our previous studies. The results of the current study suggest that EEG based markers can be applied for evaluation of disturbances in brain activity at individual level.Clinical Relevance-The indicated stability in the current study of widely used EEG-based markers at individual level suggests a promising opportunity to apply EEG as a novel method in diagnoses of brain mental disorders in clinical practice.
本研究的目的是评估基于脑电图（EEG）的标志物的个体自然变异性水平。选择了三个线性指标：α波功率变异性、频谱不对称指数、相对γ波功率，以及三种非线性方法： Higuchi分形维数、去趋势波动分析和Lempel-Ziv复杂度。在14个月内采集的15次实验中对这些标志物进行了评估。结果表明，与我们之前研究中健康组和抑郁组受试者之间的差异相比，所选五个标志物的个体自然变异性较低。当前研究结果表明，基于EEG的标志物可用于个体水平脑活动紊乱的评估。临床相关性——当前研究中所指出的广泛使用的基于EEG的标志物在个体水平的稳定性，表明在临床实践中将EEG作为诊断脑精神障碍的新方法具有广阔前景。
