Journal of Intelligent & Robotic Systems

, Volume 97, Issue 1, pp 17–32 | Cite as

Safety Control Method of Robot-Assisted Cataract Surgery with Virtual Fixture and Virtual Force Feedback

  • Yongfei Yang
  • Zhongliang Jiang
  • Yuanyuan YangEmail author
  • Xiaozhi Qi
  • Ying Hu
  • Jianjun Du
  • Bing Han
  • Guiqin LiuEmail author


Surgery is an effective means of treating cataracts and restoring vision. However, cataract surgery rate (CSR) in developing countries and regions is relatively low due to the lack of experienced high-level surgeons. In this paper, to reduce the reliance of surgery on physician experience and thereby increase CSR, a master-slave robotic system and safety control strategies with a virtual fixture and virtual force feedback are proposed to assist cataract surgery. First, the surgery is divided into four different stages with different robot control modes. Secondly, the virtual constraint area with virtual spring model in the operating stage is established, so that the doctor can distinguish the operation area where the end of the surgical instrument is located by feedback force. Thirdly, safety control algorithm guarantees that the surgical instrument strictly moves around the surgical incision point, which is regarded as a remote centre of motion, so that the cornea outside the incision point is not injured. Finally, the experimental results show that the proposed safety control strategy allows the robotic system to perform the procedure safely.


Cataract surgery Master-slave robot Virtual fixture Force feedback Remote centre of motion Safety control 


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This work is financially supported by the National Natural Science Foundation of China (Nos. 61603374, U1713218 and U1713221), the Key Fundamental Research Program of Shenzhen (Nos. JCYJ20160428144135222 and JCYJ20160427184134564), and in part by the Shenzhen Key Laboratory Project (No. ZDSYS201707271637577).


  1. 1.
    Macherner, R.: The development of pars plana vitrectomy: a personal account. Graefes Arch. Clin. Exp. Ophthalmol. 233(8), 453–468 (1995)CrossRefGoogle Scholar
  2. 2.
    Wang, W., Yan, W., Fotis, K., Prasad, N.M., Lansingh, V.C., Taylor, H.R., Finger, R.P., Facciolo, D., He, M.: Cataract surgical rate and socioeconomics: a global study. Invest. Ophthalmol. Vis. Sci. 57(14), 5872–5881 (2016)CrossRefGoogle Scholar
  3. 3.
    Community Eye Health: Cataract surgical rates. Commun. Eye Health 100(30), 88–89 (2017)Google Scholar
  4. 4.
    Tsui, I., Tsirbas, A., Mango, C.W., Schwartz, S.D., Hubschman, J.-P.: Robotic surgery in ophthalmology. In: Robot Surgery. IntechOpen (2010)Google Scholar
  5. 5.
    Bourcier, T., Chammas, J., Becmeur, P.-H., Sauer, A., Gaucher, D., Liverneaux, P., Marescaux, J., Mutter, D.: Robot-assisted simulated cataract surgery. J. Cataract. Refract. Surg. 43(4), 552–557 (2017)CrossRefGoogle Scholar
  6. 6.
    Liu, T., Li, C., Inoue, Y., Shibata, K.: Reaction force/torque sensing in a master-slave robot system without mechanical sensors. Sensors 10(8), 7134–7145 (2010)CrossRefGoogle Scholar
  7. 7.
    Balicki, M., Uneri, A., Iordachita, I., Handa, J., Gehlbach, P., Taylor, R.: Micro-force sensing in robot assisted membrane peeling for vitreoretinal surgery. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp 303–310. Springer (2010)Google Scholar
  8. 8.
    Taylor, R.H., Balicki, M.A., Handa, J.T., Gehlbach, P.L., Iordachita, I., Uneri, A.: Method for presenting force sensor information using cooperative robot control and audio feedback, February 20 2014. US Patent App. 13/813,727Google Scholar
  9. 9.
    Huang, L., Zhang, L.Y., Yang, Y., Shen, L.J., Chen, Y.Q.: Design and analysis of a robot-assisted anipulator in retinal vascular bypass surgery. In: Applied Mechanics and Materials, vol. 190, pp 673–678. Trans Tech Publ (2012)Google Scholar
  10. 10.
    Xiao, J., Yang, Y., Li, D., Huang, L., Zhang, L.: Advances and key techniques of ophthalmic microsurgical robots. J. Mech. Eng. 49(1), 15–22 (2013)CrossRefGoogle Scholar
  11. 11.
    Keenan, T., Rosen, P., Yeates, D., Goldacre, M.: Time trends and geographical variation in cataract surgery rates in england: study of surgical workload. Br. J. Ophthalmol. 91(7), 901–904 (2007)CrossRefGoogle Scholar
  12. 12.
    Yang, Y., Xu, C., Deng, S., Xiao, J.: Insertion force in manual and robotic corneal suturing. Int. J. Med. Rob. Comput. Assisted Surg. 8(1), 25–33 (2012)CrossRefGoogle Scholar
  13. 13.
    Uneri, A., Balicki, M.A., Handa, J., Gehlbach, P., Taylor, R.H., Iordachita, I.: New steady-hand eye robot with micro-force sensing for vitreoretinal surgery. In: 2010 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), pp 814–819. IEEE (2010)Google Scholar
  14. 14.
    Kong, XB, Yan, SG, Luo, SK, Su, P: Age-related changes of ocular biological structure in the elderly. Rec. Adv. Ophthalmol. 32(7), 668–672 (2012)Google Scholar
  15. 15.
    Liu, Z., Wang, B., Xu, X., Wang, C.: A study for accommodating the human crystalline lens by finite element simulation. Comput. Med. Imaging Graph. 30(6–7), 371–376 (2006)CrossRefGoogle Scholar
  16. 16.
    Nasseri, M.A., Eder, M., Nair, S., Dean, EC, Maier, M., Zapp, D., Lohmann, C.P., Knoll, A.: The introduction of a new robot for assistance in ophthalmic surgery. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5682–5685. IEEE (2013)Google Scholar
  17. 17.
    Barthel, A., Trematerra, D., Nasseri, M.A., Zapp, D., Lohmann, C.P., Knoll, A., Maier, M.: Haptic interface for robot-assisted ophthalmic surgery. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 4906–4909. IEEE (2015)Google Scholar
  18. 18.
    Nasseri, M.A., Gschirr, P, Eder, M., Nair, S., Kobuch, K., Maier, M., Zapp, D., Lohmann, C., Knoll, A.: Virtual fixture control of a hybrid parallel-serial robot for assisting ophthalmic surgery: an experimental study. In: 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, pp 732–738. IEEE (2014)Google Scholar
  19. 19.
    Charles, MW, Brown, N.: Dimensions of the human eye relevant to radiation protection (dosimetry). Phys. Med. Biol. 20(2), 202 (1975)CrossRefGoogle Scholar
  20. 20.
    Nogueira, P, Zankl, M, Schlattl, H, Vaz, P: Dose conversion coefficients for monoenergetic electrons incident on a realistic human eye model with different lens cell populations. Phys. Med. Biol. 56(21), 6919 (2011)CrossRefGoogle Scholar
  21. 21.
    Prada, R., Payandeh, S.: On study of design and implementation of virtual fixtures. Virtual Real. 13(2), 117–129 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Yongfei Yang
    • 1
    • 2
  • Zhongliang Jiang
    • 1
  • Yuanyuan Yang
    • 1
    Email author
  • Xiaozhi Qi
    • 1
  • Ying Hu
    • 1
  • Jianjun Du
    • 2
  • Bing Han
    • 3
  • Guiqin Liu
    • 3
    Email author
  1. 1.Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenChina
  2. 2.Harbin Institute of Technology at ShenzhenShenzhenChina
  3. 3.Shenzhen Eye HospitalShenzhenChina

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