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脑电图在抑郁症研究中的应用:2005年至2025年的文献计量与技术应用分析

The application of electroencephalogram in depression research: bibliometric and technological application analysis from 2005 to 2025.

作者信息

Hao Yican, Han Yanli, Huang Jian, Hao Cangcang, Yu Bo, Wei Shenting, Zhou Kuiyan

机构信息

Department of First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China.

The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China.

出版信息

Front Neurosci. 2025 Aug 21;19:1653693. doi: 10.3389/fnins.2025.1653693. eCollection 2025.

Abstract

BACKGROUND

Depression is a common mental disorder, and its diagnosis is highly dependent on subjective assessment. Electroencephalogram (EEG), as a non-invasive and economical neurophysiological tool, has garnered considerable attention in recent years in the research of auxiliary diagnosis and clinical application. However, there exists a limited number of articles that summarize this body of research. This study aims to investigate the current trends, emerging topics, and potential advancements in EEG research related to depression while also predicting the challenges that may arise within this field.

METHODS

We retrieved the literature related to depression and EEG published from April 16, 2005 to April 16, 2025 in Web of Science (WoSCC) and PubMed, and conducted data analysis and visual display using CiteSpace, VOS viewer, Bibliometrix, Scimago Graphica, Microsoft Excel 2021, and R software version 4.2.3.

RESULTS

From 2005 to 2025, 215 journals from 189 countries published papers in this field. The majority of the papers were published in , and the average citation per paper was the highest in . China contributed the most publications, but the United States had the highest citation per paper. In terms of the total number of publications, Lanzhou University contributed the most papers. The top 5 keywords were major depression, alpha asymmetry, brain, asymmetry, and anxiety. Cluster analysis indicated that the research in this field is transforming from basic electrophysiological features to clinical applications, that is, exploring the significance of EEG in the diagnosis, classification, and prediction of depression.

CONCLUSION

EEG research on depression is developing toward individualization and intelligence. In the future, efforts should be focused on standardizing processes, integrating multiple modalities, and clinical application to enhance its value in diagnosis and prognosis.

摘要

背景

抑郁症是一种常见的精神障碍,其诊断高度依赖主观评估。脑电图(EEG)作为一种非侵入性且经济的神经生理工具,近年来在辅助诊断研究和临床应用中受到了广泛关注。然而,总结这一研究领域的文章数量有限。本研究旨在探讨与抑郁症相关的脑电图研究的当前趋势、新兴主题和潜在进展,同时预测该领域可能出现的挑战。

方法

我们检索了2005年4月16日至2025年4月16日在Web of Science(WoSCC)和PubMed上发表的与抑郁症和脑电图相关的文献,并使用CiteSpace、VOS viewer、Bibliometrix、Scimago Graphica、Microsoft Excel 2021和R软件版本4.2.3进行数据分析和可视化展示。

结果

2005年至2025年,来自189个国家的215种期刊发表了该领域的论文。大多数论文发表在[具体期刊名称未给出],每篇论文的平均被引次数在[具体期刊名称未给出]最高。中国的出版物数量最多,但美国每篇论文的被引次数最高。就出版物总数而言,兰州大学发表的论文最多。前5个关键词是重度抑郁症、α波不对称性、大脑、不对称性和焦虑。聚类分析表明,该领域的研究正在从基本电生理特征向临床应用转变,即探索脑电图在抑郁症诊断、分类和预测中的意义。

结论

抑郁症的脑电图研究正朝着个体化和智能化方向发展。未来,应致力于标准化流程、整合多种模式以及临床应用,以提高其在诊断和预后方面的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fa1/12408689/a9a70d169b8b/fnins-19-1653693-g001.jpg

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