摘要
血管介入手术是一种利用导管和导丝等器械，在视觉影像引导下，通过皮肤微创穿刺进入血管，对病变部位进行诊疗的手术方式。它具有创伤小、恢复快、并发症少等优点，已成为心脑血管疾病等多种疾病的首选治疗方法。然而，由于血管的狭窄性和复杂性，在血管内部操作导管难以做到，加重了医生的认知负荷，延长了手术时间，继而增加操作者和患者的疲劳程度以及手术风险。另一方面，血管介入手术对医生操作熟练程度要求高，而可以开展大量手术的医生数量有限。这些都大大限制了血管介入手术的广泛应用。为了解决这些问题，机器人辅助血管介入手术因其精确性、灵活性、便捷性已经受到患者和医生的共同期待，是实现血管介入手术远程化、智能化、数字化的重要手段。然而，相对于血管介入手术机器人图像导航、机械臂结构等其他关键技术，力反馈技术仍然有较大空白，力反馈的缺失使其在复杂困难病变、钙化病变、慢性闭塞病变中的应用受到了限制。故笔者在此分析血管介入手术机器人力反馈技术的基本问题、实现方式和技术需求，并结合国内外研究进展，探讨了力反馈技术的发展方向，为血管介入手术机器人力反馈技术的研究提供了理论参考和实践指导。从工程设计的角度出发，从人手感知力问题和力补偿力损耗问题两个方面阐述了力反馈技术面临的基本问题，并简述人手感知力的过程、感知力的范围、力损耗原因以及力补偿方法。目前国内外关于血管介入手术机器人力反馈技术的研究还处于起步阶段，主要集中在基于机械作用、电流变液和磁流变液等方式的实验验证和系统开发上，这些方式虽然能够实现一定程度上的力反馈效果，但也存在一些局限性和不足之处：机械力反馈难以克服惯性，噪声干扰和体积庞大限制应用场景；电流变液力反馈工作电压大大超出人体安全阈值；磁流变液力反馈伴随产生的大量热气以及被动黏度产生的摩擦力干扰了准确的力呈现。因此，需要进一步探索更高效、更灵敏、更稳定、更适合远程操作的力反馈技术。另外，“局部力反馈”和“感知替代”也是值得探讨的两种有潜力的力反馈方式。对于力反馈技术实现的需求，从力传递过程出发，从传感器、力检测、力反馈三个方面进行深入分析，并结合国内外最新的研究成果进行阐述。随着人工智能、大数据、物联网、无线通信、材料学、物理学等其他交叉学科的发展，可以为血管介入手术机器人力反馈技术提供更多可能性和创新点。同时，建立基于信息融合技术的监控平台，完善相应法律法规，降低成本、临床试验验证、融合5G和虚拟现实技术等，可以使得血管介入手术机器人能够得到更广泛的应用。
根据2022年6月发布的《中国心血管健康与疾病报告2021》，心血管疾病已成为医学界公认超越癌症的人类健康头号杀手，且发病率呈上升趋
与腔镜、骨科等手术不同，血管介入手术高度依赖于装置的反馈信息。因此，如何让机器人更好地充当我们的“眼”和“手”就显得非常关键。血管介入手术机器人的视觉反馈主要依靠图像导航技术。磁共振、光学相干断层扫描、血管内超声显像、荧光成像等影像学技术可以用来发展兼容导管技术，从而提升血管介入机器人导航图像系统的性能，使机器人在手术中能看得更清楚、更远，操作更精
血管介入手术涉及血管的最内层，即内膜，由内皮和内皮下层组成，含有丰富的酶、弹性纤维、胶原纤维和少量的纵平行滑肌，有利于血液的流通。血管的内膜非常薄且易受损，一旦损伤，可能导致失血性休克、出血刺激、压迫周围组织、下游组织缺血等严重后果，甚至危及生
要实现力反馈单元，首先要了解人手能够准确地感受到力的过程。当手部皮肤受到外部机械刺激时，皮肤中的感受器群体会产生放电响应，这些信号通过神经传送给大脑进行综合分析，形成力感知。目前，血管介入手术机器人的力感知主要是压力感知（即力的可分解量化）。研
从导管或导丝接受力，到人手感知力，这个过程中会有一些力的损耗，导致反馈到人手的力精度不足，影响力反馈的透明性。这些力的损耗可能源于血管介入手术机器人中的连杆重力、机械惯性等因素引起的摩擦力。因此，需要设置相应的机械力补偿单元或引入力补偿控制算法，来平衡损耗力的力矩。根据补偿力的性质，可以分为配重补偿、弹簧补偿和辅助执行器拖动装置补
由于现有的商业操作手柄存在运动行程有限、不符合医生操作习惯、不能实现360°连续旋转（例如Touch
基于机械原理的血管介入手术机器人力反馈方式是较早发展的一种方式。Payne
因为机械力反馈反方无法解决的电机惯性问题，新兴智能材料进入到人们的视野当中。电流变液（electrorheological fluids，ERF）是一种可以通过改变外加电场改变其形态的特殊液体，一般由绝缘基础液、固体介电粒子及添加剂组
磁流变液（magnetorheological fluid，MRF）结构上与ERF类似，不同的是利用磁导原理，由软磁性颗粒、非导磁性载液和添加剂组成。羰基铁粉是软磁性颗粒的一般材
除上述的直接力反馈方式外，力反馈也可以通过其他方式实现，比如“局部力反馈”和“感知替代”。 Sankaran
无论是机械力反馈、电流变液力反馈、磁流变液力反馈或者其他力反馈技术，对于血管介入手术机器人系统而言，都需要经过以下几个步骤：力传感器检测导管/导丝与血管壁的接触力，计算机根据力信号估算反馈力，力反馈装置将反馈力传递给医生的主手，医生根据视觉和力觉反馈调整操作策略（
图1 血管介入手术机器人力反馈过程图
Figure 1 Human feedback process diagram of vascular intervention surgery machine
一般而言，应变片是组成力传感器的主要元件，具有防水性能好、体积小等优点。它们通常贴在一块弹性体上并通过检测弹性体的形变程度实现多自由度检测力。因此，弹性体的设计需要考虑与机械结构的刚度相匹配。为了减少电阻式传感器的迟滞性影响，一般采用应变片和弹性体一体化的力传感器。另外，可替代应变片的新型导电聚合物材料也在小范围内得到了应用，例如，基于炭纳米管（carbon nano tube，CNT）传感
目前，手术机器人领域的力检测方案主要有两种：直接检测和间接检测。直接检测包括基于电阻和光纤两种方式；间接检测包括基于位移以及基于执行器输入量两种方
电子科学和材料科学的飞跃进步飞速发展，以及各学科的交叉融合，促进了血管介入手术机器人力反馈技术的创新发展。这种技术有助于提高血管介入手术的精准性和微创性，为医疗外科技术的进步带来了新的机遇。例如，利用量子效
作者贡献声明
本文的主要研究目标由童静提出，并负责论文的设计、图的制作和文稿的撰写；储呈晨负责进行文稿修改和完善；李斌负责文章的质量把关和审阅、提供资金支持，对文稿的整体结构和内容有重要贡献。
利益冲突
所有作者均声明不存在利益冲突。
参考文献
马丽媛, 王增武, 樊静, 等. 《中国心血管健康与疾病报告2021》要点解读[J]. 中国全科医学, 2022, 25(27):3331-3346. doi: 10.12114/j.issn.1007-9572.2022.0506. [百度学术]
Ma LY, Wang ZW, Fan J, et al. An essential introduction to the annual report on cardiovascular health and diseases in China(2021)[J]. Chinese General Practice, 2022, 25(27):3331-3346. doi: 10.12114/j.issn.1007-9572.2022.0506. [百度学术]
Li B, Yang J, Zhao FM, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China[J]. Clin Res Cardiol, 2020, 109(5):531-538. doi: 10.1007/s00392-020-01626-9. [百度学术]
国家心血管病专业质控中心专家委员会血管外科专家工作组. 腹主动脉腔内修复手术质量评价指标体系的中国专家共识[J]. 中国普通外科杂志, 2018, 27(6):669-673. doi: 10.3978/j.issn.1005-6947.2018.06.001. [百度学术]
Working Group on Vascular Surgery, National Center for Cardiovascular Quality Improvement (NCCQI), China. Chinese experts' consensus on the evaluation index system of endovascular abdominal aortic aneurysm repair[J]. China Journal of General Surgery, 2018, 27(6):669-673. doi: 10.3978/j.issn.1005-6947.2018.06.001. [百度学术]
Klein LW, Goldstein JA, Haines D, et al. SCAI multi-society position statement on occupational health hazards of the catheterization laboratory: shifting the paradigm for healthcare workers' protection[J]. J Am Coll Cardiol, 2020, 75(14):1718-1724. doi: 10.1016/j.jacc.2020.02.015. [百度学术]
Pappone C, Augello G, Gugliotta F, et al. Robotic and magnetic navigation for atrial fibrillation ablation. How and why?[J]. Expert Rev Med Devices, 2007, 4(6):885-894. doi: 10.1586/17434440.4.6.885. [百度学术]
Hwang J, Kim JY, Choi H. A review of magnetic actuation systems and magnetically actuated guidewire- and catheter-based microrobots for vascular interventions[J]. Intel Serv Robotics, 2020, 13(1):1-14. doi: 10.1007/s11370-020-00311-0. [百度学术]
Swaminathan RV, Rao SV. Robotic-assisted transradial diagnostic coronary angiography[J]. Catheter Cardiovasc Interv, 2018, 92(1):54-57. doi: 10.1002/ccd.27480. [百度学术]
Mendes Pereira V, Cancelliere NM, Nicholson P, et al. First-in-human, robotic-assisted neuroendovascular intervention[J]. J NeuroIntervent Surg, 2020, 12(4):338-340. doi: 10.1136/neurintsurg-2019-015671.rep. [百度学术]
CorPath 200 Robotic System for Percutaneous Coronary Interventions Green Lighted in U.S.[EB/OL]. Available at: https://www.medgadget.com/2012/07/corpath-200-robotic-system-for-percutaneous-coronary-interventions-green-lighted-in-u-s.html. DOI: 10.33963/kp.a2021.0057 [百度学术]
Weisz G, Metzger DC, Caputo RP, et al. Safety and feasibility of robotic percutaneous coronary intervention: precise (Percutaneous Robotically-Enhanced Coronary Intervention) Study[J]. J Am Coll Cardiol, 2013, 61(15):1596-1600. doi: 10.1016/j.jacc.2012.12.045. [百度学术]
何昊, 叶子健, 舒畅. 血管介入手术机器人系统关键技术及研发现状[J]. 中国普通外科杂志, 2021, 30(12):1477-1484. doi: 10.7659/j.issn.1005-6947.2021.12.012. [百度学术]
He H, Ye ZJ, Shu C. Essential techniques and current research situation in robotic endovascular systems[J]. China Journal of General Surgery, 2021, 30(12): 1477-1484. doi: 10.7659/j.issn.1005-6947.2021.12.012. [百度学术]
Beyar R, Gruberg L, Deleanu D, et al. Remote-control percutaneous coronary interventions[J]. J Am Coll Cardiol, 2006, 47(2):296-300. doi: 10.1016/j.jacc.2005.09.024. [百度学术]
张舒怡, 曲新凯, 韩文正. 血管介入机器人辅助技术的研究进展[J]. 中国心血管病研究, 2021, 19(8):764-768. doi: 10.3969/j.issn.1672-5301.2021.08.019. [百度学术]
Zhang SY, Qu XK, Han WZ. Research progress of vascular interventional surgical robotic system[J]. Chinese Journal of Cardiovascular Research, 2021, 19(8):764-768. doi: 10.3969/j.issn.1672-5301.2021.08.019. [百度学术]
刘建民, 杨鹏飞, 李翯. 全面认识血管损伤, 推动学科融合发展[J]. 第二军医大学学报, 2021, 42(2):122-126. doi: 10.16781/j.0258-879x.2021.02.0122. [百度学术]
Liu JM, Yang PF, Li H. To fully understand vascular impairment from the perspective of discipline integration[J]. Academic Journal of Naval Medical University, 2021, 42(2):122-126. doi: 10.16781/j.0258-879x.2021.02.0122. [百度学术]
Vinjamuri R. Advances in Motor Neuroprostheses[M]. Cham: Springer International Publishing, 2020. doi: 10.1007/978-3-030-38740-2. [百度学术]
Arakelian V. Gravity compensation in robotics[J]. Adv Robotics, 2016, 30(2):79-96. DOI: 10.1080/01691864.2015.1090334 [百度学术]
Mashayekhi A, Nahvi A, Yazdani M, et al. VirSense: a novel haptic device with fixed-base motors and a gravity compensation system[J]. Ind Robot, 2014, 41(1):37-49. doi: 10.1108/IR-02-2013-328. [百度学术]
Fukushima S, Sekiguchi H, Saito Y, et al. Online compensation of gravity and friction for haptics with incremental position sensors[C]//2017 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP). Auckland, New Zealand: IEEE Press, 2017:1-6. doi: 10.1109/M2VIP.2017.8211458. [百度学术]
Wang GL, Li YF, Bi DX. Support vector network enhanced adaptive friction compensation[C]//Proceedings 2006 IEEE International Conference on Robotics and Automation. Orlando, USA: IEEE, 2006: 3699-3704. doi: 10.1109/ROBOT.2006.1642267. [百度学术]
Dong A, Du ZJ, Yan ZY. Friction modeling and compensation for haptic master manipulator based on deep Gaussian process[J]. Mech Mach Theory, 2021, 166:104480. doi: 10.1016/j.mechmachtheory.2021.104480. [百度学术]
3D Systems. Touch-HAPTIC DEVICE [EB/OL]. (2016-06-09)[2023-06-02]. Available at: https://cn.3dsystems.com/haptics-devices/touch. [百度学术]
Zhao Y, Mei ZY, Luo XX, et al. Remote vascular interventional surgery robotics: a literature review[J]. Quant Imaging Med Surg, 2022, 12(4):2552-2574. doi: 10.21037/qims-21-792. [百度学术]
Payne CJ, Rafii-Tari H, Yang GZ. A force feedback system for endovascular catheterisation[C]//2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. Vilamoura-Algarve, Portugal: IEEE, 2012: 1298-1304. doi: 10.1109/IROS.2012.6386149. [百度学术]
Yang C, Guo SX, Bao XQ. An isomorphic interactive device for the interventional surgical robot after in vivo study[J]. Micromachines, 2022, 13(1):111. doi: 10.3390/mi13010111. [百度学术]
Abiri A, Pensa J, Tao AN, et al. Multi-modal haptic feedback for grip force reduction in robotic surgery[J]. Sci Rep, 2019, 9:5016. doi: 10.1038/s41598-019-40821-1. [百度学术]
韩翻珍, 杨秀娟, 丛丰, 等. 以专利技术信息分析电流变液的现状[J]. 中国科技产业, 2023(2):70-73. doi: 10.16277/j.cnki.cn11-2502/n.2023.02.019. [百度学术]
Han FZ, Yang XJ, Cong F, et al. Analysis of the present situation of electrorheological fluids with patent technical information[J]. Science & Technology Industry of China, 2023(2):70-73. doi: 10.16277/j.cnki.cn11-2502/n.2023.02.019 [百度学术]
Liang Y, Huang D, Zhou X, et al. Efficient electrorheological technology for materials, energy, and mechanical engineering: from mechanisms to applications[J]. Engineering, 2022, 2022: S2095809922003526. doi: 10.1016/j.eng.2022.01.014. [百度学术]
Zakaria NAC, Komeda T, Low CY, et al. Development of foolproof catheter guide system based on mechatronic design[J]. Prod Eng Res Devel, 2013, 7(1):81-90. doi: 10.1007/s11740-012-0430-6. [百度学术]
Salunkhe H, Kolekar A, Thikane S. Electrorheological fluids: properties, technology and modern applications[J]. IRJET, 2023, 10(2):129-134. [百度学术]
张进秋, 张建, 孔亚男, 等. 磁流变液及其应用研究综述[J]. 装甲兵工程学院学报, 2010, 24(2):1-6. doi: 10.3969/j.issn.1672-1497.2010.02.001. [百度学术]
Zhang JQ, Zhang J, Kong YN, et al. Summarization of magnetorheological fluid and its application[J]. Journal of Academy of Armored Force Engineering, 2010, 24(2):1-6. doi: 10.3969/j.issn.1672-1497.2010.02.001. [百度学术]
Guo SX, Song Y, Yin XC, et al. A novel robot-assisted endovascular catheterization system with haptic force feedback[J]. IEEE Trans Robotics, 2019, 35(3):685-696. doi: 10.1109/TRO.2019.2896763. [百度学术]
Shi P, Guo SX, Jin XL, et al. A two-channel haptic force interface for endovascular robotic systems[C]//2020 IEEE International Conference on Mechatronics and Automation (ICMA). Beijing, China: IEEE, 2020: 1602-1606. doi: 10.1109/ICMA49215.2020.9233544. [百度学术]
Hooshiar A, Alkhalaf A, Dargahi J. Development and assessment of a stiffness display system for minimally invasive surgery based on smart magneto-rheological elastomers[J]. Mater Sci Eng C Mater Biol Appl, 2020, 108:110409. doi: 10.1016/j.msec.2019.110409. [百度学术]
Hooshiar A, Payami A, Dargahi J, et al. Magnetostriction-based force feedback for robot-assisted cardiovascular surgery using smart magnetorheological elastomers[J]. Mech Syst Signal Process, 2021, 161:107918. doi: 10.1016/j.ymssp.2021.107918. [百度学术]
Liu Z, Wang S, Feng F, et al. A magnetorheological fluid based force feedback master robot for vascular interventional surgery[J]. J Intell Robot Syst, 2022, 106(1):20. doi: 10.1007/s10846-022-01716-y. [百度学术]
Zhang LS, Gu SX, Guo SX, et al. A magnetorheological fluids-based robot-assisted catheter/guidewire surgery system for endovascular catheterization[J]. Micromachines (Basel), 2021, 12(6):640. doi: 10.3390/mi12060640. [百度学术]
Gao Q, Zhan Y, Song Y, et al. An MR fluid based master manipulator of the vascular intervention robot with haptic feedback[C]//2021 IEEE International Conference on Mechatronics and Automation (ICMA). Takamatsu, Japan: IEEE, 2021:158-163. doi: 10.1109/ICMA52036.2021.9512709. [百度学术]
Sankaran NK, Chembrammel P, Kesavadas T. Force calibration for an endovascular robotic system with proximal force measurement[J]. Int J Med Robotics Comput Assist Surg, 2020, 16(2):e2045. doi: 10.1002/rcs.2045. [百度学术]
Dagnino G, Liu J, Abdelaziz MEMK, et al. Haptic feedback and dynamic active constraints for robot-assisted endovascular catheterization[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain: IEEE, 2019:1770-1775. doi: 10.1109/IROS.2018.8593628. [百度学术]
Yu HY, Wang HB, Zhang W, et al. Master-slave system research of a vascular interventional surgical robot[C]//2018 IEEE International Conference on Real-time Computing and Robotics (RCAR). Kandima, Maldives: IEEE, 2018:469-473. doi: 10.1109/RCAR.2018.8621763. [百度学术]
Kanoun O, Bouhamed A, Ramalingame R, et al. Review on conductive polymer/CNTs nanocomposites based flexible and stretchable strain and pressure sensors[J]. Sensors (Basel), 2021, 21(2):341. doi: 10.3390/s21020341. [百度学术]
Zhou KK, Dai K, Liu CT, et al. Flexible conductive polymer composites for smart wearable strain sensors[J]. SmartMat, 2020, 1(1):e1010. doi: 10.1002/smm2.1010. [百度学术]
Tang ZX, Wang SX, Li M, et al. Development of a distal tri-axial force sensor for minimally invasive surgical palpation[J]. IEEE Trans Med Robotics Bionics, 2022, 4(1):145-155. doi: 10.1109/TMRB.2022.3142361. [百度学术]
付宜利, 李坤, 潘博, 等. 微创手术机器人力检测与力反馈技术研究现状[J]. 机器人, 2014, 36(1):117-128. doi: 10.3724/SP.J.1218.2014.00117. [百度学术]
Fu YL, Li K, Pan B, et al. A survey of force sensing and force feedback technology for robot-assisted minimally invasive surgical system[J]. Robot, 2014, 36(1):117-128. doi: 10.3724/SP.J.1218.2014.00117. [百度学术]
Yin XC, Guo SX, Song Y. Magnetorheological fluids actuated haptic-based teleoperated catheter operating system[J]. Micromachines, 2018, 9(9):465. doi: 10.3390/mi9090465. [百度学术]
Song Y, Guo SX, Yin XC, et al. Performance evaluation of a robot-assisted catheter operating system with haptic feedback[J]. Biomed Microdevices, 2018, 20(2):50. doi: 10.1007/s10544-018-0294-4. [百度学术]
Shi L, Li Z, Chen M, et al. Quantum effect-based flexible and transparent pressure sensors with ultrahigh sensitivity and sensing density[J]. Nat Commun, 2020, 11(1):3529. doi: 10.1038/s41467-020-17298-y. [百度学术]
Gauglitz G. The new generation: quantum sensors[J]. Anal Bioanal Chem, 2021, 413(23):5679-5680. doi: 10.1007/s00216-021-03554-7. [百度学术]
Fogliano F, Besga B, Reigue A, et al. Ultrasensitive nano-optomechanical force sensor operated at dilution temperatures[J]. Nat Commun, 2021, 12(1):4124. doi: 10.1038/s41467-021-24318-y. [百度学术]
Beltrán SM, Slepian MJ, Taylor RE. Extending the capabilities of molecular force sensors via DNA nanotechnology[J]. Crit Rev Biomed Eng, 2020, 48(1):1-16. doi: 10.1615/critrevbiomedeng.2020033450. [百度学术]
Algamili AS, Khir MHM, Dennis JO, et al. A review of actuation and sensing mechanisms in MEMS-based sensor devices[J]. Nanoscale Res Lett, 2021, 16(1):16. doi: 10.1186/s11671-021-03481-7. [百度学术]
Ye X, Li YY, Zhang Y, et al. A comprehensive review: recent developments of biomimetic sensors[J]. J Bionic Eng, 2022, 19(4):853-876. doi: 10.1007/s42235-022-00181-5. [百度学术]