静息态脑电图全自动与视觉控制的预处理和后处理的可靠性
Reliability of fully automated versus visually controlled pre- and post-processing of resting-state EEG.
作者信息
Hatz F, Hardmeier M, Bousleiman H, Rüegg S, Schindler C, Fuhr P
机构信息
Department of Neurology, Hospital of the University of Basel, Switzerland.
Department of Neurology, Hospital of the University of Basel, Switzerland; Swiss Tropical and Public Health Institute, University of Basel, Switzerland.
出版信息
Clin Neurophysiol. 2015 Feb;126(2):268-74. doi: 10.1016/j.clinph.2014.05.014. Epub 2014 Jun 2.
OBJECTIVE
To compare the reliability of a newly developed Matlab® toolbox for the fully automated, pre- and post-processing of resting state EEG (automated analysis, AA) with the reliability of analysis involving visually controlled pre- and post-processing (VA).
METHODS
34 healthy volunteers (age: median 38.2 (20-49), 82% female) had three consecutive 256-channel resting-state EEG at one year intervals. Results of frequency analysis of AA and VA were compared with Pearson correlation coefficients, and reliability over time was assessed with intraclass correlation coefficients (ICC).
RESULTS
Mean correlation coefficient between AA and VA was 0.94±0.07, mean ICC for AA 0.83±0.05 and for VA 0.84±0.07.
CONCLUSION
AA and VA yield very similar results for spectral EEG analysis and are equally reliable. AA is less time-consuming, completely standardized, and independent of raters and their training.
SIGNIFICANCE
Automated processing of EEG facilitates workflow in quantitative EEG analysis.
目的
比较新开发的用于静息态脑电图全自动预处理和后处理的Matlab®工具箱（自动分析，AA）与涉及视觉控制预处理和后处理（VA）的分析的可靠性。
方法
34名健康志愿者（年龄：中位数38.2岁（20 - 49岁），82%为女性）每隔一年进行连续三次256通道静息态脑电图检查。将AA和VA的频率分析结果用Pearson相关系数进行比较，并用组内相关系数（ICC）评估随时间的可靠性。
结果
AA和VA之间的平均相关系数为0.94±0.07，AA的平均ICC为0.83±0.05，VA的平均ICC为0.84±0.07。
结论
AA和VA在脑电图频谱分析中产生非常相似的结果，且可靠性相当。AA耗时更少，完全标准化，并且独立于评分者及其培训。
意义
脑电图的自动处理有助于定量脑电图分析中的工作流程。
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