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目的:通过对焦虑障碍高危人群、焦虑障碍患者和健康人群全频域自发脑电信号进行频域分析，探索可用于识别焦虑障碍的特征性频段。方法:2019年12月10日至2020年5月7日选取焦虑障碍高危人群(焦虑高危组，n n＝19)、焦虑障碍患者(阳性对照组，n n＝14)、健康正常人(正常对照组，n n＝19)作为研究对象。使用焦虑状态-特质问卷(state-trait anxiety inventory，S-TAI)、军事应激反应性焦虑预测量表(military stress anxiety predictive scale，MSAPS)对所有被试进行评估，并在问卷评估过程进行脑电监测。统计分析使用SPSS20.0统计软件，三组间脑电功率差异分析采用单因素方差分析和两两比较。n 结果:三组在Delta[(2.11±0.66)μVn 2，(2.52±0.38)μVn 2，(2.73±0.47)μVn 2]、Theta[(1.31±0.43)μVn 2，(1.52±0.28)μVn 2，(1.67±0.35)μVn 2]、Alpha[(1.05±0.44)μVn 2，(1.29±0.25)μVn 2，(1.45±0.55)μVn 2]、Beta-1[(0.69±0.16)μVn 2，(0.86±0.18)μVn 2，(0.99±0.27)μVn 2]、Beta-2[(0.55±0.15)μVn 2，(0.67±0.18)μVn 2，(0.75±0.20)μVn 2]、Gamma频段[(0.31±0.09)μVn 2，(0.40±0.14)μVn 2，(0.45±0.16)μVn 2]Cz电极处的脑电功率差异均有统计学意义(n F＝3.80～9.21，均n P<0.05)。经Bonferroni校正后两两比较，Beta-1频段下，焦虑高危组与正常对照组之间的脑电功率差异有统计学意义(n P＝0.03)。n 结论:焦虑障碍高危人群和焦虑障碍患者的脑电信号均在Cz处的Beta-1频段与健康人群有显著差异。这种脑电信号的差异可为焦虑高危人群的识别和焦虑障碍的诊断提供有利的客观支持。“,”Objective:To explore the characteristic bands that could be used to identify anxiety disorders through frequency domain analysis of spontaneous EEG in high-risk individuals with anxiety disorder, patients with anxiety disorders and healthy people.Methods:From December 10, 2019 to May 7, 2020, 19 high-risk individuals with anxiety disorder (high-risk anxiety group), 14 patients with anxiety disorder (positive control group) and 19 healthy people (normal control group) were selected as the research objects.The State Trait Anxiety Inventory (S-TAI) and military stress anxiety predictive scale (MSAPS) were applied to all subjects.EEG was detected during the questionnaire evaluation.SPSS 20.0 statistical software was used.One way ANOVA and pairwise comparison were used to analyze the difference of EEG power among the three groups.Results:The differences of EEG power among the three groups at Cz electrodes in Delta((2.11±0.66)μVn 2, (2.52±0.38)μVn 2, (2.73±0.47)μVn 2), Theta((1.31±0.43)μVn 2, (1.52±0.28)μVn 2, (1.67±0.35)μVn 2), Alpha((1.05±0.44)μVn 2, (1.29±0.25)μVn 2, (1.45±0.55)μVn 2), Beta-1((0.69±0.16)μVn 2, (0.86±0.18)μVn 2, (0.99±0.27)μVn 2), Beta-2((0.55±0.15)μVn 2, (0.67±0.18)μVn 2, (0.75±0.20)μVn 2) and Gamma band((0.31±0.09)μVn 2, (0.40±0.14)μVn 2, (0.45±0.16)μVn 2) were statistically significant(n F=3.80-9.21, all n P<0.05). After Bonferroni correction, the difference of EEG power between high-risk anxiety group and normal control group was statistically significant in Beta-1 band (n P=0.03).n Conclusion:The EEG signals of patients with anxiety disorder and anxiety disorders are significantly different from those of healthy people at Beta-1 frequencies at Cz.The difference of EEG signals can provide objective support for the identification of high-risk of anxiety and the diagnosis of anxiety disorder.