静息态脑电在意识诊断中的临床应用

doi:10.3969/j.issn.0258-8021.2021.02.04

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Abstract The accurate diagnosis of patients with disorder of consciousness (DOC) is of great significance for the treatment plan and outcome, so it is very necessary to develop a reliable method to assess the level of consciousness. In this work, fifty patients diagnosed with DOC (25 vegetable state (VS) patients and 25 minimally consciousness state (MCS) patients) were enrolled. The EEG data were obtained through Bispectral index (BIS) monitor; information complexity and relative power were calculated. The differences of EEG characteristics between MCS and VS groups were analyzed by two sample t-test, and the quantitative relationship between EEG characteristics and clinical scores was analyzed by Pearson correlation analysis. Exploring EEG characteristics to distinguish the states of consciousness. The EEG characteristics were used to build machine-learning model and explore its potential in clinical diagnosis. The results showed that permutation entropy (PE), permutation Lempel-Ziv complexity (PLZC) and the relative power of gamma band were able to distinguish different states of consciousness (PE: 0.71±0.07, 0.75±0.07, P<0.01; PLZC: 0.53±0.07, 0.56±0.06, P<0.01; gamma: 0.13±0.07, 0.16±0.06, P<0.01). PE shows the highest correlation (r=0.81, P<0.05). The area under the ROC curve (AUC) and accuracy (ACC) of consciousness classification model based on PE (AUC=0.931, ACC=0.92) was better than that of BIS (AUC=0.905, ACC=0.90). In conclusion, the resting EEG can be used as an important method for the diagnosis of consciousness.

Key words： resting state electroencephalogram disorders of consciousness(DOC) diagnosis

Received: 21 March 2020

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R318

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	Articles by authors
	Wang Yong
	Liang Zhenhu
	Xia Xiaoyu
	Bai Yang
	Yang Yi
	Liu Yangfeng
	He Jianghong
	Li Xiaoli

Cite this article:

Wang Yong,Liang Zhenhu,Xia Xiaoyu, et al. Clinical Application of Resting EEG in Consciousness Diagnosis[J]. Chinese Journal of Biomedical Engineering, 2021, 40(2): 154-162.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2021.02.04 OR http://cjbme.csbme.org/EN/Y2021/V40/I2/154

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