文章摘要
陈学莹*,齐晓英**,史周晰*,独盟盟*.基于微状态的抑郁症静息态脑电信号分析[J].高技术通讯(中文),2024,34(4):379~385
基于微状态的抑郁症静息态脑电信号分析
Analysis of resting EEG signals for depression based on microstates
  
DOI:10. 3772 / j. issn. 1002-0470. 2024. 04. 005
中文关键词: 抑郁症(MDD); 静息态脑电(EEG); 脑电信号处理; 微状态; 聚类
英文关键词: major depressive disorder(MDD), resting-state electroencephalogram(EEG), EEG signal processing, microstate, clustering
基金项目:
作者单位
陈学莹* (*陕西科技大学数学与数据科学学院西安 710021) (**延安大学医学院延安 716000) 
齐晓英**  
史周晰*  
独盟盟*  
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中文摘要:
      抑郁症(MDD)患者存在认知功能障碍,但其瞬时神经异常活动尚未研究清楚,对此采用脑电(EEG)微状态方法对抑郁症患者的脑电数据进行研究。比较22名抑郁症患者和25名正常人的128导闭眼脑电数据微状态特征,进行差异性分析并探索与量表得分之间的相关性。结果发现,相对于健康对照组,抑郁症患者微状态C的出现次数和涵盖比更高,且与其他微状态之间的转换概率较高,而其微状态D的平均持续时间较低,且与微状态B之间的转换次数减少。此外,微状态C和微状态D与抑郁量表和焦虑量表均呈显著相关性,表明基于脑电微状态方法可以捕捉到抑郁症患者异常大脑动态特性,为抑郁症临床早期诊治提供客观参考。
英文摘要:
      Patients with major depressive disorder(MDD) have cognitive dysfunction, but current studies did not clearly investigate its temporal abnormal neurological activity. In response to this problem, this paper uses the electroencephalogram (EEG) microstate method to study the EEG data of patients with major depression. This paper compares the microstate characteristics of 128-channel EEG data from 22 patients with major depressive disorder and 25 healthy controls, performs statistical analysis and explores correlations with scale scores. Results show that compared with healthy controls, the occurrence and coverage of microstate C in major depressive disorder group are higher, and the transition probabilities between other microstates and C are also higher, while the average duration of microstate D is lower and the number of transitions between D and microstate B significantly decreases. In addition, microstates C and microstates D are significantly correlated with the depression scale and anxiety scale. The results show that the EEG-based microstate method can capture the abnormal brain dynamic characteristics of depressed patients, and provide an objective reference for the early clinical diagnosis and treatment of depression.
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