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Shared control of a medical robot with haptic guidance

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Tele-operation of robotic surgery reduces the radiation exposure during the interventional radiological operations. However, endoscope vision without force feedback on the surgical tool increases the difficulty for precise manipulation and the risk of tissue damage. The shared control of vision and force provides a novel approach of enhanced control with haptic guidance, which could lead to subtle dexterity and better maneuvrability during MIS surgery.

Methods

The paper provides an innovative shared control method for robotic minimally invasive surgery system, in which vision and haptic feedback are incorporated to provide guidance cues to the clinician during surgery. The incremental potential field (IPF) method is utilized to generate a guidance path based on the anatomy of tissue and surgical tool interaction. Haptic guidance is provided at the master end to assist the clinician during tele-operative surgical robotic task.

Results

The approach has been validated with path following and virtual tumor targeting experiments. The experiment results demonstrate that comparing with vision only guidance, the shared control with vision and haptics improved the accuracy and efficiency of surgical robotic manipulation, where the tool-position error distance and execution time are reduced.

Conclusions

The validation experiment demonstrates that the shared control approach could help the surgical robot system provide stable assistance and precise performance to execute the designated surgical task. The methodology could also be implemented with other surgical robot with different surgical tools and applications.

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References

  1. Uçar BY (2012) Percutaneous surgery: A safe procedure for trigger finger? N Am J Med Sci 4(9):401

    Article  PubMed  PubMed Central  Google Scholar 

  2. DiMaio SP, Salcudean SE (2005) Interactive simulation of needle insertion models. Biomed Eng IEEE Trans 52(7):1167–1179

    Article  Google Scholar 

  3. Lanfranco AR, Castellanos AE, Desai JP, Meyers WC (2004) Robotic surgery: a current perspective. Ann surg 239(1):14–21. doi:10.1097/01.sla.0000103020.19595.7d

    Article  PubMed  PubMed Central  Google Scholar 

  4. Xiong L, Chui C, Teo C, Lau D (2013) Incremental potential field based haptic guidance for medical simulation. In: IEEE/SICE international symposium on system integration (SII). IEEE, pp 772–777

  5. Xiong L, Chui C-K, Fu Y, Teo C-L, Li Y (2015) Modeling of human artery tissue with probabilistic approach. Comput Biol Med 59:152–159

    Article  PubMed  Google Scholar 

  6. Marescaux J, Smith MK, Fölscher D, Jamali F, Malassagne B, Leroy J (2001) Telerobotic laparoscopic cholecystectomy: initial clinical experience with 25 patients. Ann Surg 234(1):1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Marescaux J, Leroy J, Rubino F, Smith M, Vix M, Simone M, Mutter D (2002) Transcontinental robot-assisted remote telesurgery: feasibility and potential applications. Ann Surg 235(4):487

    Article  PubMed  PubMed Central  Google Scholar 

  8. Yamamoto T, Abolhassani N, Jung S, Okamura AM, Judkins TN (2012) Augmented reality and haptic interfaces for robot—assisted surgery. Int J Med Robot Comput Assist Surg 8(1):45–56

    Article  Google Scholar 

  9. Okamura AM (2009) Haptic feedback in robot-assisted minimally invasive surgery. Curr Opin Urol 19(1):102–107

    Article  PubMed  PubMed Central  Google Scholar 

  10. Lamata P, Freudenthal A, Cano A, Kalkofen D, Schmalstieg D, Naerum E, Samset E, Gómez EJ, Sánchez-Margallo FM, Furtado H (2010) Augmented reality for minimally invasive surgery: overview and some recent advances. INTECH Open Access Publisher, Vienna

    Google Scholar 

  11. Suzuki S, Suzuki N, Hattori A, Hayashibe M, Konishi K, Kakeji Y, Hashizume M (2005) Tele-surgery simulation with a patient organ model for robotic surgery training. Int J Med Robot Comput Assist Surg 1(4):80–88

    Article  CAS  Google Scholar 

  12. Ming L, Ishii M, Taylor RH (2007) Spatial motion constraints using virtual fixtures generated by anatomy. Robot IEEE Trans 23(1):4–19

    Article  Google Scholar 

  13. Wagner CR, Stylopoulos N, Howe RD (2002) The role of force feedback in surgery: analysis of blunt dissection. In: Symposium on haptic interfaces for virtual environment and teleoperator systems. Citeseer, pp 73–79

  14. Kübler B, Seibold U, Hirzinger G (2005) Development of actuated and sensor integrated forceps for minimally invasive robotic surger. Int J Med Robot Comput Assist Surg 1(3):96–107

    Article  Google Scholar 

  15. Ribeiro F, Lopes A (2013) Haptic guidance in a collaborative robotic system. In: Neto P, Moreira A (eds) Robotics in smart manufacturing, vol 371., Communications in computer and information scienceSpringer, Berlin, pp 101–112

    Chapter  Google Scholar 

  16. Powell D, O’Malley MK (2012) The task-dependent efficacy of shared-control haptic guidance paradigms. Haptics IEEE Trans 5(3):208–219

    Article  CAS  Google Scholar 

  17. Bowyer SA, Davies BL, Rodriguez y, Baena F (2014) Active constraints/virtual fixtures: a survey. Robot IEEE Trans 30(1):138–157

    Article  Google Scholar 

  18. Li M, Ishii M, Taylor RH (2007) Spatial motion constraints using virtual fixtures generated by anatomy. Robot IEEE Trans 23(1):4–19

    Article  Google Scholar 

  19. Safavi A, Zadeh MH (2015) Model-based haptic guidance in surgical skill improvement. In: Systems, man, and cybernetics (SMC), 2015 IEEE international conference on, 9-12 Oct. 2015, pp 1104–1109

  20. Yang T, Liu J, Huang W, Yang L, Chui CK, Ang Jr MH, Su Y, Chang SK (2013) Mechanism of a learning robot manipulator for laparoscopic surgical training. In: Frontiers of intelligent autonomous systems. Springer, pp 297–308

  21. Sawashima H, Hori Y, Sunahara H, Oie Y (1997) Characteristics of UDP packet loss: effect of tcp traffic. In: Proceedings of INET’97: the seventh annual conference of the internet society

  22. Ge SS, Cui YJ (2002) Dynamic motion planning for mobile robots using potential field method. Auton Robots 13(3):207–222

    Article  Google Scholar 

  23. Latombe JC (2012) Robot motion planning (Vol. 124). Springer Science & Business Media, Newyork

  24. Koren Y, Borenstein J (1991) Potential field methods and their inherent limitations for mobile robot navigation. In: Robotics and automation, 1991. Proceedings 1991 IEEE international conference on, IEEE, pp 1398–1404

  25. Xiong L, Chui C-K, Teo C-L (2013) Reality based modeling and simulation of gallbladder shape deformation using variational methods. Int J Comput Assist Radiol Surg 8(5):857–865

    Article  PubMed  Google Scholar 

  26. Cleary K, Nguyen C (2001) State of the art in surgical robotics: clinical applications and technology challenges. Comput Aid Surg 6(6):312–328

    Article  CAS  Google Scholar 

  27. Rossi A, Trevisani A, Zanotto V (2005) A telerobotic haptic system for minimally invasive stereotactic neurosurgery. Int J Med Robot Comput Assist Surg 1(2):64–75

    Article  CAS  Google Scholar 

  28. Kesner SB, Howe RD (2014) Robotic catheter cardiac ablation combining ultrasound guidance and force control. Int J Robot Res 33(4):631–644

  29. Cole GA, Harrington K, Su H, Camilo A, Pilitsis JG, Fischer GS (2014) Closed-loop actuated surgical system utilizing real-time in-situ MRI guidance. In: Experimental Robotics. Springer, pp 785–798

  30. Webster RJ, Memisevic J, Okamura AM (2005) Design considerations for robotic needle steering. In: Robotics and automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE international conference on, 18–22 April 2005, pp 3588–3594

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Correspondence to Linfei Xiong or Chee Kong Chui.

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The authors declare that they have no conflict of interest. Informed consent was obtained from all individual participants included in the study.

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Xiong, L., Chng, C.B., Chui, C.K. et al. Shared control of a medical robot with haptic guidance. Int J CARS 12, 137–147 (2017). https://doi.org/10.1007/s11548-016-1425-0

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  • DOI: https://doi.org/10.1007/s11548-016-1425-0

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