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Chinese Journal of Medical Instrumentation                                         2026年 第50卷 第2期

                                                     医   疗   机   器   人


              文章编号:1671-7104(2026)02-0119-10

                                  中医药临床证据转化多功能机器人

                                    (Multi-RevRobot)研发与应用




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             【作     者】 季昭臣 ,胡海殷 ,贺志远 ,张雅姿 ,吴晓蕾 ,桑子凡 ,胡静 ,王喆 ,薛运华 ,张俊华                              1,2
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                          1 天津中医药大学,天津市,301617
                          2 现代中医药海河实验室,天津市,301617
                          3 天津大学,天津市,300354
                          4 南开大学,天津市,300071
             【摘     要】 目的 在政策导向与技术发展背景下,研发中医药临床证据转化多功能机器人(Multi-RevRobot),提升中
                          医药临床证据转化效率,增强其应用便捷性。方法 从感知系统、控制系统、执行系统、动力系统、交互系
                          统等方面设计并开发Multi-RevRobot样机;布局通用式模型接口并对接垂类大模型和知识库,实现智能交
                          互;将人工势场法与强化学习有机结合,实现机器人全局路径规划和局部避障决策的高效协同,满足各类
                          场景下的部署应用要求。结果 Multi-RevRobot具有智能交互、报告生成、多场景适配等特点,为中医药临
                          床证据转化提供实体化解决方案,在不同场景发挥相应作用。结论 Multi-RevRobot有望作为临床和科研助
                          手,服务于医生、研究者、患者等群体,提高中医药相关工作效率,助力中医药证据智能、高效转化应用。
             【关   键   词】 中医药;临床证据;循证医学;机器人
             【中图分类号】 R2; TP242.6
             【文献标志码】 A                                                         doi: 10.12455/j.issn.1671-7104.250372
                Development and Application of Multi-RevRobot for the Translation of
                             Clinical Evidence of Traditional Chinese Medicine

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             【   Authors  】 JI Zhaochen , HU Haiyin , HE Zhiyuan , ZHANG Yazi , WU Xiaolei , SANG Zifan , HU Jing , WANG Zhe ,
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                          XUE Yunhua , ZHANG Junhua 1,2
                          1 Tianjin University of Traditional Chinese Medicine, Tianjin, 301617
                          2 Haihe Laboratory of Modern Chinese Medicine, Tianjin, 301617
                          3 Tianjin University, Tianjin, 300354
                          4 Nankai University, Tianjin, 300071
             【  Abstract  】 Objective Under the background of policy guidance and technological development, the Multi-RevRobot
                          for the translation of clinical evidence of traditional Chinese medicine (TCM) was developed to enhance
                          the  efficiency  and  applicability  of  clinical  evidence  translation  in  TCM.  Methods  A  prototype  of  Multi-
                          RevRobot  was  designed  and  developed.  This  involved  components  such  as  the  perception  system,
                          control system, execution system, power system, and interaction system. Universal model interfaces were
                          integrated to connect with vertical large models and knowledge bases, enabling intelligent interaction. The
                          artificial potential field method was combined with reinforcement learning to achieve efficient coordination
                          between the robot’s global path planning and local obstacle-avoidance decision-making. This allows the
                          robot  to  be  deployed  and  applied  in  various  scenarios.  Results  Multi-RevRobot  features  intelligent
                          interaction,  report  generation,  and  multi-scenario  adaptability.  It  provides  a  practical  solution  for  TCM
                          clinical  evidence  translation  and  plays  corresponding  roles  in  various  scenarios.  Conclusion  Multi-
                          RevRobot is expected to serve as a clinical and research assistant for doctors, researchers, patients, and
                          other groups. It can improve the efficiency of TCM-related work and facilitate the intelligent and efficient
                          translation and application of TCM evidence.

              收稿日期:2025-05-31
              基金项目:国家中医药管理局中医药创新团队及人才支持计划项目–国家中医药多学科交叉创新团队(ZYYCXTD-D-202204);2025现代
                      中医药海河实验室第一批科技项目(25HHZYSS00023);国家自然科学基金项目(82505806)
              作者简介:季昭臣,E-mail: robin_johnson@foxmail.com
              通信作者:张俊华,E-mail: zjhtcm@foxmail.com


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