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大型回顾性医院脑电图队列中后头部优势节律的全自动峰值频率估计

Fully automatic peak frequency estimation of the posterior dominant rhythm in a large retrospective hospital EEG cohort.

作者信息

Zibrandtsen Ivan C, Kjaer Troels W

机构信息

Neurological Department, Zealand University Hospital, Roskilde, Denmark.

Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.

出版信息

Clin Neurophysiol Pract. 2020 Dec 3;6:1-9. doi: 10.1016/j.cnp.2020.11.001. eCollection 2021.

DOI:10.1016/j.cnp.2020.11.001
PMID:33385100
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7771042/
Abstract

OBJECTIVE

To develop and test a fully automated method for estimation of the peak frequency of the posterior dominant rhythm (PDR) in a large retrospective EEG cohort.

METHODS

Thresholding was used to select suitable EEG data segments for spectral estimation for electrode O1 and O2. A random sample of 100 peak frequency estimates were blindly rated by two independent raters to validate the results of the automatic PDR peak frequency estimates. We investigated the relationship with age, sex and binary EEG classification.

RESULTS

There were 9197 eligible EEGs which resulted in a total of 6104 PDR peak frequency estimates. The relationship between automatic estimates and age was found to be consistent with the literature. The correlation between human ratings and automatic scoring was very high, rho = 0.94-0.95. There was a sex difference of d = 0.33 emerging at puberty with females having a faster PDR peak frequency than males.

CONCLUSIONS

Fully automatic PDR peak frequency estimation not dependent on annotated EEG produced results that are very close to human ratings.

SIGNIFICANCE

PDR peak frequency can be automatically estimated. A compiled version of the algorithm is included as an app for independent use.

摘要

目的

开发并测试一种用于在大型回顾性脑电图队列中估计后头部优势节律（PDR）峰值频率的全自动方法。

方法

使用阈值法为电极O1和O2选择适合进行频谱估计的脑电图数据段。由两名独立评估者对100个峰值频率估计值的随机样本进行盲法评分，以验证自动PDR峰值频率估计的结果。我们研究了其与年龄、性别和脑电图二元分类的关系。

结果

有9197份符合条件的脑电图，共得出6104个PDR峰值频率估计值。发现自动估计值与年龄之间的关系与文献一致。人工评分与自动评分之间的相关性非常高，rho = 0.94 - 0.95。青春期出现了d = 0.33的性别差异，女性的PDR峰值频率比男性快。

结论

不依赖于标注脑电图的全自动PDR峰值频率估计所产生的结果与人工评分非常接近。

意义

PDR峰值频率可以自动估计。算法的编译版本作为一个独立使用的应用程序包含在内。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/022cf7e15b3d/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/8c9c354166b3/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/fabd1ed46d8f/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/e6f4fc9f634d/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/e76affd0735c/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/c88e434c5b8c/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/700edc2f06b3/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/a99b68e283a9/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/022cf7e15b3d/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/8c9c354166b3/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/fabd1ed46d8f/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/e6f4fc9f634d/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/e76affd0735c/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/c88e434c5b8c/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/700edc2f06b3/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/a99b68e283a9/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ecd3/7771042/022cf7e15b3d/gr8.jpg

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