中国康复理论与实践2025，Vol.31Issue(11)：1314-1321,8.DOI:10.3969/j.issn.1006-9771.2025.11.008
定量脑电图在轻度认知障碍数字化筛查中的应用
Application of quantitative electroencephalography in digital screening for mild cognitive impairment
摘要
Abstract
Objective To explore the quantitative electroencephalography(qEEG)characteristics of the prefrontal cortex in patients with mild cognitive impairment(MCI)during digital screening tasks for MCI screening. Methods A total of 592 MCI patients(MCI group)and 317 normal cognitively elderly individuals(control group)were recruited from 40 communities in Nanjing,Jiangsu Province,from July to August,2024.All participants were as-sessed using Montreal Cognitive Assessment-Beijing Version(MoCA-BJ).Prefrontal EEG data were collected using a portable EEG device,and power spectral analysis was performed via Fast Fourier Transform.An XG-Boost algorithm was employed to construct an MCI identification model based on qEEG power features,and the model's performance was evaluated using receiver operating characteristic(ROC)curve. Results Compared with the control group,prefrontal δ,α,and β band power increased during screening tasks in MCI group(P<0.05);δ power was negatively correlated with MoCA-BJ total scores,and visuospatial/executive func-tion,attention and delayed recall scores(r=-0.269,-0.169,-0.133,-0.171,P<0.001);α power was negative-ly correlated with MoCA-BJ total scores,attention and delayed recall scores(r=-0.113,-0.075,-0.091,P<0.05).The XGBoost model based on δ and α power was excellent in MCI identification,with an area under the curve of 0.91,accuracy of 0.81,precision of 0.89,F1 score of 0.84,recall of 0.80,and specificity of 0.81. Conclusion MCI patients exhibit increased power in the prefrontal δ and α frequency bands during digital screening tasks,which is associated with cognitive decline.An XGBoost model based on qEEG power features can enable early prediction of MCI.关键词
老年人/轻度认知障碍/数字化筛查/定量脑电图/XGBoost算法Key words
elderly/mild cognitive impairment/digital screening/quantitative electroencephalography/XGBoost分类
临床医学引用本文复制引用
顾剑鹏,宋玉磊,殷海燕,尹婷婷,孙凤仪,杨冰清,赵鸣晖,徐桂华,柏亚妹..定量脑电图在轻度认知障碍数字化筛查中的应用[J].中国康复理论与实践,2025,31(11):1314-1321,8.基金项目
1.国家重点研发项目(No.2023YFC3603600) （No.2023YFC3603600）
2.国家自然科学基金面上项目(No.72174095) （No.72174095）
3.江苏省社会发展面上项目(No.BE2022802) （No.BE2022802）
4.江苏省研究生科研创新计划课题(No.YCX25_2388) Supported by National Key Research and Development Program of China(No.2023YFC3603600),National Natural Science Foundation of China(General)(No.72174095),Jiangsu Provincial Social Development Project(General)(No.BE2022802),and Jiangsu Postgraduate Research&Practice Innovation Program(No.YCX25_2388) （No.YCX25_2388）
