Force-detecting gripper and force feedback system for neurosurgery applications
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Purpose For the application of less invasive robotic neurosurgery to the resection of deep-seated tumors, a prototype system of a force-detecting gripper with a flexible micromanipulator and force feedback to the operating unit will be developed.
Methods Gripping force applied on the gripper is detected by strain gauges attached to the gripper clip. The signal is transmitted to the amplifier by wires running through the inner tube of the manipulator. Proportional force is applied on the finger lever of the operating unit by the surgeon using a bilateral control program. A pulling force experienced by the gripper is also detected at the gripper clip. The signal for the pulling force is transmitted in a manner identical to that mentioned previously, and the proportional torque is applied on the touching roller of the finger lever of the operating unit. The surgeon can feel the gripping force as the resistance of the operating force of the finger and can feel the pulling force as the friction at the finger surface.
Results A basic operation test showed that both the gripping force and pulling force were clearly detected in the gripping of soft material and that the operator could feel the gripping force and pulling force at the finger lever of the operating unit.
Conclusions A prototype of the force feedback in the microgripping manipulator system has been developed. The system will be useful for removing deep-seated brain tumors in future master–slave-type robotic neurosurgery.
KeywordsNeurosurgery Robotic surgery Brain tumor Manipulator Force feedback
The authors would like to thank Y. Yamashita, Y. Fujihira, K. Tanaka, N. Sugiyama, T. Hanyu, K. Azuma, T. Osawa, Y. Tanaka, K. Takahashi, W. Ueno, and T. Fujii for their efforts in developing the manipulator system.
Conflict of interest
There is no conflict of interest in this study.
- 4.Haidegger T, Kovacs L, Fordos G, Bnyo Z, Kazanzides P (2008) Future trends in robotic neurosurgery. 14th Nordic-Baltic conference on biomedical engineering and, medical physics. pp 229–233Google Scholar
- 5.Hongo K, Kakizawa Y, Koyama J, Nishizawa K, Tajima F, Fujie MG, Kobayashi S (2001) Microscopic-manipulator system for minimally invasive neurosurgery. Computer assisted radiology and surgery, Amsterdam, excerpta medica, pp 265–269Google Scholar
- 9.Hongo K, Goto T, Kakizawa Y, Koyama J (2011) Microsurgery-assisting robotics (NeuRobot): current status and future perspective. Jpn J Neurosurg 20(4):270–274 (in Japanese)Google Scholar
- 10.Kan K, Fujie MG, Tajima F, Nishizawa K, Kawai T, Shose A, Takakura K, Kobayashi S, Dohi T (2001) Development of HUMAN system with the three micro manipulator for minimally invasive neurosurgery. Computer assisted radiology and surgery, Amsterdam, excerpta medica. pp 144–149Google Scholar
- 11.Nishizawa K, Fujie MG, Hongo K, Dohi T, Iseki H (2006) Development of surgical manipulator system “HUMAN” for clinical neurosurgery. JMAJ 49(11–12):335–344Google Scholar
- 12.Morita A, Sora S, Mitsuishi M, Warisawa S, Suruman K, Asai D, Arata J, Baba S, Takahashi H, Mochizuki R, Kirino T (2005) Microsurgical robotic system for the deep surgical field: development of a prototype and feasibility studies in animal and cadaveric models. J Neurosurg 103:320–327PubMedCrossRefGoogle Scholar
- 13.Okayasu H, Okamoto J, Iseki M, Fujie MG (2005) Development of a hydraulically-driven flexible manipulator for neurosurgery. J Robotics Mechatron 17(2):149–157Google Scholar
- 14.Arata J, Fischer GS, Papademetris X et al (2009) Open GTLink: an open network protocol for image-guided therapy environment. Int J Med Robotics Comput Assist Surg (2009) doi: 10.1002/rcs.274
- 16.Tavakoli M, Patel RV, Moallem M (2004) Design issues in a haptics-based master-slave system for minimally invasive surgery. 2004 IEEE international conference on robotics and automation pp 371–376Google Scholar
- 17.Takahashi H, Warisawa M, Mitsuishi M, Arata J, Hashizume M (2006) Development of high dexterity minimally invasive surgical system with augmented force feedback capability. The first IEEE/RAS-EMBS international conference on biomedical robotics and biomechatronics. pp 284–289Google Scholar
- 18.Thielmann S, Seibold U, Hslinger R, Passig G, Bahls T, Joerg S, Nickl M, Nothhelfer A, Hagn U, Hirzinger G (2010) MICA-A new generation of versatile instruments in robotic surgery. The 2010 IEEE/RSJ international conference on intelligent robots and systems, pp 871–878Google Scholar
- 19.Tholey G, Desai JP (2007) A modular, automated laparoscopic grasper with three-dimensional force measurement capability. IEEE international conference on robotics and automation pp 250–255Google Scholar
- 20.Hashiguchi D, Tadano K, Kawashima K (2011) A prototype of pneumatically-driven forceps manipulator with force sensing capability using a simple flexible joint. 2011 IEEE/RSJ international conference on intelligent robots and systems. pp 931–936Google Scholar
- 21.Yoneyama T, Watanabe T, Kagawa H, Hamada J, Hayashi Y, Nakada M (2011) Force detecting gripper and flexible micro manipulator for neurosurgery. 33rd annual international conference of the IEEE EMBS pp 6695–6699Google Scholar
- 23.Ohara N, Nakazawa K, Morikawa Y, Kitajima M (2010) Bilateral control considering interference with environment for microsurgery. Trans Jpn Soc Mech Eng Ser C 76(766):78–83Google Scholar
- 24.Soza G, Grosso R, Mimsky C, Hastreiter P, Fahlbusch R, Greiner G (2005) Determination of the elasticity parameters of brain tissue with combined simulation and registration. Int J Med Robotics Comput Assist Surg 1(3):87–95Google Scholar
- 25.Colgate JE (1993) Robust impedance shaping telemanipulation. IEEE Trans Robotics Autom 9(4):374–384 Google Scholar
- 26.Provancher WR, Sylvester ND (2009) Fingerpad skin stretch increases the perception of virtual friction. IEEE Trans Haptics 2(4):212–223Google Scholar