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图学学报 ›› 2026, Vol. 47 ›› Issue (2): 251-263.DOI: 10.11996/JG.j.2095-302X.2026020251

• 综述 • 上一篇    下一篇

基于CiteSpace的国内外手术机器人交互设计分析比较研究

王一芮, 华馨怡, 汤天宇, 王奕霖, 闫祉祺, 耿子涵, 陈星宇, 杨建明, 孙博文()   

  1. 北京理工大学设计与艺术学院北京 100081
  • 收稿日期:2025-05-22 接受日期:2025-10-29 出版日期:2026-04-30 发布日期:2026-05-20
  • 通讯作者:孙博文,E-mail:sunbowen@bit.edu.cn
  • 基金资助:
    北京理工大学研究生科研水平和创新能力提升专项计划(2024YCXZ014)

A comparative analysis of domestic and international research on surgical robot interaction design using CiteSpace

WANG Yirui, HUA Xinyi, TANG Tianyu, WANG Yilin, YAN Zhiqi, GENG Zihan, CHEN Xingyu, YANG Jianming, SUN Bowen()   

  1. School of Design and Arts, Beijing Institute of Technology, Beijing 100081, China
  • Received:2025-05-22 Accepted:2025-10-29 Published:2026-04-30 Online:2026-05-20
  • Contact: SUN Bowen,E-mail:sunbowen@bit.edu.cn
  • Supported by:
    Special Program for Enhancing the Research Skills and Innovation Capabilities of Graduate Students at Beijing Institute of Technology(2024YCXZ014)

摘要:

针对手术机器人在人机交互设计领域的发展现状,开展了系统的比较与可视化研究。基于Web of Science和CNKI数据库,检索手术机器人交互设计相关文献,运用文献计量分析法与内容分析法,结合VOSviewer和CiteSpace的可视化功能,绘制知识图谱,从合作网络分布、研究热点主题和时区演化3个维度揭示手术机器人交互设计领域的研究格局与发展趋势。结果表明,国外手术机器人交互设计研究起步较早,各研究机构之间联系紧密,研究内容精细化,更关注技术驱动研发;相比之下,国内该领域研究起步较晚,研究机构之间互动相对较少,且研究内容较分散,侧重于理论研究和用户体验。研究指出,未来应强化跨学科协同创新,融合智能语音识别、高精度视觉与触觉数字化、运动轨迹智能规划、机器学习与大数据建模等前沿技术,以推动手术机器人交互设计的智能化、精确化与人性化发展。

关键词: 多模态人机交互设计, 知识图谱, 视觉触觉数字化, 机器学习, 运动轨迹智能规划

Abstract:

To address the current development status of surgical robot interaction design, a systematic comparative and visualized analysis was conducted. Based on the Web of Science and CNKI databases, literature related to surgical robot interaction design was retrieved. Bibliometric and content analysis methods were applied in combination with the visualization functions of VOSviewer and CiteSpace to construct knowledge maps. From three dimensions-collaboration network distribution, research hotspot themes, and temporal evolution the research landscape and development trends in this field were revealed. The results showed that international research on surgical robot interaction design had started earlier, with close institutional collaborations and more refined, technology-driven research focuses. In contrast, domestic research in this area was initiated later, with weaker institutional cooperation, more scattered topics, and a greater emphasis on theoretical exploration and user experience. It was concluded that future research should strengthen interdisciplinary collaborative innovation and integrate advanced technologies such as intelligent speech recognition, high-precision visual and haptic digitization, intelligent motion trajectory planning, machine learning, and big data modeling to promote the intelligent, precise, and human-centered development of surgical robot interaction design.

Key words: multimodal human-computer interaction design, knowledge mapping, visual-haptic digitization, machine learning, intelligent motion trajectory planning

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