A Study on the Evolution and Trends of EEG Techniques in Autism Spectrum Disorder Research

LI Yue-tong; CAI Chang; LI Rui

doi:10.3969/j.issn.1672-4933.2026.02.008

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A Study on the Evolution and Trends of EEG Techniques in Autism Spectrum Disorder Research

Artificial Intelligence Rehabilitation Education | 更新时间：2026-07-30

- A Study on the Evolution and Trends of EEG Techniques in Autism Spectrum Disorder Research
- Chinese Scientific Journal of Hearing and Speech Rehabilitation Vol. 24, Issue 2, Pages: 152-157(2026)
- 作者机构：
  
  华中师范大学教育大数据应用技术国家工程研究中心武汉 430079
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1672-4933.2026.02.008
  CLC： R494
- Received：30 December 2025，
  
  Online First：17 March 2026，
  
  Published：15 March 2026
- 稿件说明：
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李悦彤,蔡畅,李睿.孤独症谱系障碍脑电图技术演化与趋势研究[J].中国听力语言康复科学杂志,2026,24(02):152-157.

LI Yue-tong,CAI Chang,LI Rui.A Study on the Evolution and Trends of EEG Techniques in Autism Spectrum Disorder Research[J].Chinese Scientific Journal of Hearing and Speech Rehabilitation,2026,24(02):152-157.
李悦彤,蔡畅,李睿.孤独症谱系障碍脑电图技术演化与趋势研究[J].中国听力语言康复科学杂志,2026,24(02):152-157. DOI： 10.3969/j.issn.1672-4933.2026.02.008.

LI Yue-tong,CAI Chang,LI Rui.A Study on the Evolution and Trends of EEG Techniques in Autism Spectrum Disorder Research[J].Chinese Scientific Journal of Hearing and Speech Rehabilitation,2026,24(02):152-157. DOI： 10.3969/j.issn.1672-4933.2026.02.008.

摘要

孤独症谱系障碍（ASD）是起病于儿童早期、影响社交沟通与行为发展的重要神经发育障碍，亟需客观量化的神经生物学证据支撑分层评估与精准干预。脑电图技术能够以无创、高时间分辨率检测大脑神经活动，为干预效果监测和客观评估指标提供神经生物学基础。本文系统梳理近20年国内脑电图应用于ASD研究的主题结构与热点演化特征，采用CiteSpace开展年度发文、关键词共现、聚类与突现分析。结果显示，2005～2025年国内ASD脑电研究总体呈上升趋势，2018年后进入快速发展期，2016～2025年发文占比约78.0%。关键词共现网络结构具有一定聚合性，高频与关键枢纽词主要包括孤独症、儿童、脑电图等。聚类分析形成10个主要主题簇，热点由早期的任务诱发成分与差异描述逐步拓展至脑网络、相干性等计算化指标，并在近年聚焦癫痫等共病、亚型与基因线索、生活质量与睡眠障碍、情绪测量及脑电信号处理，呈现由机制探索走向智能化评估与临床转化的趋势。在未来研究中，应在流程规范化、可解释模型构建等方面持续推进，以提升证据质量，加速评估框架落地。

Abstract

Autism spectrum disorder (ASD) is a major neurodevelopmental condition with onset in early childhood that affects the development of social communication and behavior

and it urgently requires objective

quantifiable neurobiological evidence to support stratified assessment and precision interventions. Electroencephalography (EEG)

a noninvasive technique that captures neural activity with high temporal resolution

provides a neurobiological basis for monitoring intervention effects and establishing objective evaluation indicators. This study systematically reviewed the thematic structure and evolution of research hotspots in China over the past two decades regarding the application of EEG to ASD research. CiteSpace was used to analyze annual publication trends

keyword co-occurrence

clustering

and burst detection. The results showed that domestic EEG research on ASD exhibited an overall upward trend from 2005 to 2025

entering a period of rapid growth after 2018. Publications from 2016 to 2025 accounted for approximately 78.0% of the total. The keyword co-occurrence network demonstrated a certain degree of clustering

with high-frequency and central hub keywords including autism

children

and electroencephalography. The Cluster analysis identified ten major thematic clusters

with hotspots expanding from early work on task-evoked components and differential descriptions to computational indices

and more recently focusing on comorbidities such as epilepsy

subtypes and genetic clues

quality of life and sleep disorders

emotion measurement

and EEG signal processing. Overall

the field is shifting from mechanistic exploration to intelligent assessment and clinical translation. Future research should continue to advance standardized workflows and interpretable model development to improve the quality of evidence and accelerate the implementation of evaluation frameworks.

关键词

Keywords

references

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