《中国康复理论与实践》

《中国康复理论与实践》 ›› 2025, Vol. 31 ›› Issue (5): 573-580.doi: 10.3969/j.issn.1006-9771.2025.05.010

• 循证研究 • 上一篇    下一篇

人工智能在孤独症谱系障碍儿童诊断与干预中应用的文献计量分析

周波1,2, 佘万斌3, 向松柏1,4()   

  1. 1.乐山师范学院特殊教育学院，四川乐山市 614000
    2.西华师范大学教育学院，四川南充市 637009
    3.乐山师范学院教育科学学院，四川乐山市 614000
    4.特殊教育语言智能四川省哲学社会科学重点实验室，四川乐山市 614000
  • 收稿日期:2024-12-19 修回日期:2025-03-31 出版日期:2025-05-25 发布日期:2025-05-26
  • 通讯作者: 向松柏(1989-)，男，汉族，四川巴中市人，博士，副教授。E-mail： xiangsongbaipsy@126.com
  • 作者简介:周波(1999-)，男，汉族，四川巴中市人，硕士研究生，主要研究方向：融合教育。
  • 基金资助:
    全国教育科学"十四五"规划青年课题(ECA230515)

Application of artificial intelligence in diagnosis and intervention for children with autism spectrum disorder: a bibliometric analysis

ZHOU Bo1,2, SHE Wanbin3, XIANG Songbai1,4()   

  1. 1. College of Special Education, Leshan Normal University, Leshan, Sichuan 614000, China
    2. College of Education, China West Normal University, Nanchong, Sichuan 637009, China
    3. College of Educational Sciences, Leshan Normal University, Leshan, Sichuan 614000, China
    4. Sichuan Key Laboratory of Philosophy and Social Sciences for Language Intelligence in Special Education, Leshan, Sichuan 614000, China
  • Received:2024-12-19 Revised:2025-03-31 Published:2025-05-25 Online:2025-05-26
  • Contact: XIANG Songbai, E-mail: xiangsongbaipsy@126.com
  • Supported by:
    The 14th Five Year Plan of National Education Sciences (Youth)(ECA230515)

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摘要：

目的 探讨人工智能技术在孤独症谱系障碍(ASD)儿童诊断与干预领域的研究现状、热点和发展趋势。
方法 检索Web of Science核心合集数据库关于人工智能与ASD儿童诊断与干预主题相关的文献，时间范围2024年10月28日前。采用CiteSpace 6.3.R1软件进行分析。
结果 共获得符合标准的文献219篇。年发文量呈快速增长趋势。Peter Washington、Dennis P. Wall、Antonie D. Kline、Haik Kalantarian和Qandeel Tariq等作者发文量位居前列。美国在该领域的影响力显著，斯坦福大学、埃及知识库、哈佛大学、伦敦大学等是核心研究机构。研究热点集中于机器学习、深度学习、虚拟现实等技术在社交沟通、情绪识别、语言康复等方面的应用。研究经历了技术验证(2012年至2016年)、技术深化(2017年至2020年)和融合创新(2021年至2024年) 3个阶段。
结论 人工智能技术在ASD儿童诊断与干预领域研究发展较快。机器学习、深度学习等算法能显著提升诊断精确度，虚拟现实、机器人辅助等技术能有效改善干预效果。当前研究已从单一技术验证阶段发展到多模态技术融合应用阶段，形成了以美国为主导、多国参与的国际化研究格局。

关键词: 孤独症谱系障碍, 儿童, 人工智能, 文献计量学

Abstract:

Objective To explore the research status, hotspots and development of artificial intelligence in the field of diagnosis and intervention for children with autism spectrum disorder (ASD).
Methods Literatures about the topic of artificial intelligence for diagnosis and intervention for ASD were retrieved from Web of Science Core Collection till October 28, 2024, and analyzed using CiteSpace 6.3.R1.
Results A total of 219 articles were included, showing a fluctuating upward trend. Peter Washington, Dennis P. Wall, Antonie D. Kline, Haik Kalantarian and Qandeel Tariq were the authors with the most publications. The United States was dominant in the field, and Stanford University, the Egyptian Knowledge Bank, Harvard University and University of London were the core institutions. The researches focused on the application of machine learning, deep learning, virtual reality and other technologies in social communication, emotion recognition and speech rehabilitation. The development of the researches could be classified as three phases: validation (2012-2016), deepening (2017-2020) and integration and innovation (2021-2024).
Conclusion Artificial intelligence has developed significantly in the field of diagnosis and intervention for children with ASD. Algorithms such as machine learning and deep learning can improve diagnostic accuracy, and technologies such as virtual reality and robot-assistance can improve intervention outcomes. The researches are evolving from a single technology validation to a multimodal technology integration, led by the United States with the participation of many countries.

Key words: autism spectrum disorder, children, artificial intelligence, bibliometrics

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