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管理头皮记录中的肌电图干扰:一种识别精神病或其他障碍的可靠β和γ EEG 特征的方法。

Managing electromyogram contamination in scalp recordings: An approach identifying reliable beta and gamma EEG features of psychoses or other disorders.

机构信息

College of Science and Engineering, Flinders University, Adelaide, South Australia, Australia.

Medical Device Research Institute, Flinders University, Adelaide, South Australia, Australia.

出版信息

Brain Behav. 2022 Sep;12(9):e2721. doi: 10.1002/brb3.2721. Epub 2022 Aug 2.

Abstract

OBJECTIVE

In publications on the electroencephalographic (EEG) features of psychoses and other disorders, various methods are utilized to diminish electromyogram (EMG) contamination. The extent of residual EMG contamination using these methods has not been recognized. Here, we seek to emphasize the extent of residual EMG contamination of EEG.

METHODS

We compared scalp electrical recordings after applying different EMG-pruning methods with recordings of EMG-free data from 6 fully paralyzed healthy subjects. We calculated the ratio of the power of pruned, normal scalp electrical recordings in the six subjects, to the power of unpruned recordings in the same subjects when paralyzed. We produced "contamination graphs" for different pruning methods.

RESULTS

EMG contamination exceeds EEG signals progressively more as frequencies exceed 25 Hz and with distance from the vertex. In contrast, Laplacian signals are spared in central scalp areas, even to 100 Hz.

CONCLUSION

Given probable EMG contamination of EEG in psychiatric and other studies, few findings on beta- or gamma-frequency power can be relied upon. Based on the effectiveness of current methods of EEG de-contamination, investigators should be able to reanalyze recorded data, reevaluate conclusions from high-frequency EEG data, and be aware of limitations of the methods.

摘要

目的

在有关精神病和其他障碍的脑电图(EEG)特征的出版物中,使用了各种方法来减少肌电图(EMG)的干扰。但是,尚未认识到这些方法残留的 EMG 干扰的程度。在这里,我们旨在强调 EEG 残留 EMG 干扰的程度。

方法

我们比较了应用不同的 EMG 修剪方法后头皮电记录与 6 名完全瘫痪的健康受试者的无 EMG 数据记录。我们计算了在 6 名受试者中修剪后的头皮电记录的功率与同一受试者在瘫痪时未修剪记录的功率之比。我们为不同的修剪方法制作了“污染图”。

结果

EMG 干扰随着频率超过 25 Hz 以及距离顶点的增加而逐渐超过 EEG 信号。相比之下,即使在 100 Hz 时,中央头皮区域的 Laplacian 信号也不会受到干扰。

结论

鉴于在精神病学和其他研究中 EEG 可能存在 EMG 干扰,因此很少可以依赖有关β或γ频带功率的发现。基于 EEG 去污染的当前方法的有效性,研究人员应该能够重新分析记录的数据,重新评估高频 EEG 数据的结论,并意识到方法的局限性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f885/9480942/403d6d784b1f/BRB3-12-e2721-g001.jpg

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