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Development of a mechanical decoupling surgical scissors for robot-assisted minimally invasive surgery

Published online by Cambridge University Press:  31 May 2021

Xingze Jin
Affiliation:
School of Mechanical and Aerospace Engineering, Jilin University, Changchun City, China
Mei Feng*
Affiliation:
School of Mechanical and Aerospace Engineering, Jilin University, Changchun City, China
Zhiwu Han
Affiliation:
College of Biological and Agricultural Engineering, Jilin University, Changchun City, China
Ji Zhao
Affiliation:
School of Mechanical and Automation, Northeastern University, Shenyang City, China
Hankun Cao
Affiliation:
College of Automotive Engineering, Jilin University, Changchun City, China
Yaoyuan Zhang
Affiliation:
College of Automotive Engineering, Jilin University, Changchun City, China
*
*Corresponding author. Email: fengmei@jlu.edu.cn

Abstract

In minimally invasive surgery, surgical instruments with a wrist joint have better flexibility. However, the bending motion of the wrist joint causes a coupling motion between the end-effector and wrist joint, affecting the accuracy of the movement of the surgical instrument. Aiming at this problem, a new gear train decoupling method is proposed in the paper, which can automatically compensate for the coupled motion in real-time. Based on the performance tests of the instrument prototype, a series of decoupling effects tests are carried out. The test results show that the surgical instrument has excellent decoupling ability and stable performance.

Type
Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

Cadiere, G. B., Himpens, J., Germay, O., Izizaw, R., Degueldre, M., Vandromme, J., Capelluto, E. and Bruyns, J., “Feasibility of robotic laparoscopic surgery: 146 cases World,” J. Surg. 25(11), 14671477 (2001).Google Scholar
Lanfranco, A. R., Castellanos, A. E., Desai, J. P. and Meyers, W. C., “Robotic surgery: A current perspective,” Ann. Surg. 239(1), 1421 (2004).CrossRefGoogle ScholarPubMed
Simillis, C., Constantinides, V. A., Tekkis, P. P., Darzi, A., Lovegrove, R., Jiao, L. and Antoniou, A., “Laparoscopic versus open hepatic resections for benign and malignant neoplasms–a meta-analysis,” Surgery 141(2), 203211 (2007).CrossRefGoogle ScholarPubMed
Donias, H. W., Karamanoukian, H. L., Ancona, G. D" and Hoover, E. L., “Minimally invasive mitral valve surgery: From Port Access to fully robotic-assisted surgery,” Angiology 54(1), 93101 (2003).CrossRefGoogle ScholarPubMed
Menon, M., Tewari, A., Peabody, J. O., Shrivastava, A., Kaul, S., Bhandari, A. and Hemal, A. K., “Vattikuti Institute prostatectomy, a technique of robotic radical prostatectomy for management of localized carcinoma of the prostate: Experience of over 1100 cases,” Urol. Clin. North Am. 31(4), 701717 (2004).CrossRefGoogle ScholarPubMed
Badani, K. K., Kaul, S. and Menon, M., “Evolution of robotic radical prostatectomy: Assessment after 2766 procedures,” Cancer 110(9), 19511958 (2007).CrossRefGoogle ScholarPubMed
Bell, M. C., Torgerson, J., Seshadri-Kreaden, U., Suttle, A. W. and Hunt, S., “Comparison of outcomes and cost for endometrial cancer staging via traditional laparotomy, standard laparoscopy and robotic techniques,” Gynecol. Oncol. 111(3), 407411 (2008).CrossRefGoogle ScholarPubMed
Haber, G. P., Crouzet, S. and Gill, I. S., “Laparoscopic and robotic assisted radical cystectomy for bladder cancer: A critical analysis,” Eur. Urol. 54(1), 5462 (2008).CrossRefGoogle ScholarPubMed
Benway, B. M., Bhayani, S. B., Rogers, C. G., Dulabon, L. M., Patel, M. N., Lipkin, M., Wang, A. J. and Stifelman, M. D., “Robot assisted partial nephrectomy versus laparoscopic partial nephrectomy for renal tumors: A multi-institutional analysis of perioperative outcomes,” J. Urol. 182(3), 866872 (2009).CrossRefGoogle ScholarPubMed
Dogangil, G., Davies, B. L. and Rodriguez y Baena, F., “A review of medical robotics for minimally invasive soft tissue surgery,” Proc. Inst. Mech. Eng. H 224(5), 653679 (2010).CrossRefGoogle ScholarPubMed
Aitchison, L. P., Cui, C. K., Arnold, A., Nesbitt-Hawes, E. and Abbott, J., “The ergonomics of laparoscopic surgery: A quantitative study of the time and motion of laparoscopic surgeons in live surgical environments,” Surg. Endoscopy 30(11), 19 (2017).Google Scholar
Takazawa, S., Ishimaru, T., Harada, K., Deie, K. and Hinoki, A., “Evaluation of surgical devices using an artificial pediatric thoracic model: A comparison between robot-assisted thoracoscopic suturing versus conventional video-assisted thoracoscopic suturing,” J. Laparoendoscopic Adv. Surg. Tech. Part A 28(5), 622627 (2018).CrossRefGoogle ScholarPubMed
Nelson, C. A., Laribi, M. A. and Zeghloul, S., “Multi-robot system optimization based on redundant serial spherical mechanism for robotic minimally invasive surgery,” Robotica 37(7), 12021213 (2018).CrossRefGoogle Scholar
Rana, R., Gaur, P., Agarwal, V. and Parthasarathy, H., “Tremor estimation and removal in robot-assisted surgery using lie groups and EKF,” Robotica 37(11), 19041921 (2019).CrossRefGoogle Scholar
Torabi, A., Khadem, M., Zareinia, K., Sutherland, G. R. and Tavakoli, M., “Using a redundant user interface in teleoperated surgical systems for task performance enhancement,” Robotica 38(10), 18801894 (2020).CrossRefGoogle Scholar
Binder, J., Bräutigam, R., Jonas, D. and Bentas, W., “Robotic surgery in urology: Fact or fantasy?,” BJU Int. 94(8), 11831187 (2004).CrossRefGoogle ScholarPubMed
Hockstein, N. G., Nolan, J. P., O’Malley, B. W. Jr and Woo, Y. J., “Robotic microlaryngeal surgery: A technical feasibility study using the daVinci surgical robot and an airway mannequin,” Laryngoscope 115(5), 780785 (2005).CrossRefGoogle Scholar
Smith, J. M., Stein, H., Engel, A. M., McDonough, S. and Lonneman, L., “Totally endoscopic mitral valve repair using a robotic-controlled atrial retractor,” Ann. Thorac. Surg. 84(2), 633637 (2007).CrossRefGoogle ScholarPubMed
Hompes, R., Rauh, S. M., Hagen, M. E. and Mortensen, N. J., “Preclinical cadaveric study of transanal endoscopic da Vinci(R) surgery,” Br. J. Surg. 99(8), 11441148 (2012).CrossRefGoogle Scholar
Madhani, A. J., Niemeyer, G. and Kenneth Salisbury, J. Jr, “The Black Falcon: A Teleoperated Surgical Instrument for Minimally Invasive Surgery,” 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems, 1998. Proceedings (1998).Google Scholar
Harada, K., Tsubouchi, K., Fujie, M. G. and Chiba, T., “Micro Manipulators for Intrauterine Fetal Surgery in an Open MRI,” IEEE International Conference on Robotics & Automation (2005).CrossRefGoogle Scholar
Luo, H., Ding, J. and Wang, S., “A Master-Slave Robot System for Minimally Invasive Laryngeal Surgery,” IEEE International Conference on Robotics & Biomimetics (2009).CrossRefGoogle Scholar
He, C., Wang, S., Xing, Y. and Wang, X., “Kinematics analysis of the coupled tendon-driven robot based on the product-of-exponentials formula,” Mech. Mach. Theory 60(none), 90–111 (2013).CrossRefGoogle Scholar
Cao, Z., Xiao, Q., Huang, R. and Zhou, M., “Robust neuro-optimal control of underactuated snake robots with experience replay,” IEEE Trans. Neural Netw. Learn. Syst. 29(1), 208217 (2018).CrossRefGoogle ScholarPubMed
Ma, X., Song, C., Chiu, P. W. and Li, Z., “Autonomous flexible endoscope for minimally invasive surgery with enhanced safety,” IEEE Rob. Autom. Lett. 4(3), 26072613 (2019).CrossRefGoogle Scholar
Tierney Michael, J., Cooper, T., Julian, C., Blumenkranz Stephen, J., Guthart Gary, S. and Younge Robert, G., Surgical robotic tools, data architecture, and use (2001).Google Scholar
Noonan, D. P., Mylonas, G. P., Darzi, A. and Yang, G. Z., “Gaze Contingent Articulated Robot Control for Robot Assisted Minimally Invasive Surgery,” IEEE/RSJ International Conference on Intelligent Robots & Systems (2008).CrossRefGoogle Scholar
Li, K., Pan, B., Zhang, F., Gao, W., Fu, Y. and Wang, S., “A novel 4-DOF surgical instrument with modular joints and 6-Axis Force sensing capability,” Int. J. Med. Rob. 13(1) (2017).CrossRefGoogle Scholar
Hagn, U., Konietschke, R., Tobergte, A., Nickl, M., Jorg, S., Kubler, B., Passig, G., Groger, M., Frohlich, F., Seibold, U., Le-Tien, L., Albu-Schaffer, A., Nothhelfer, A., Hacker, F., Grebenstein, M. and Hirzinger, G., “DLR MiroSurge: A versatile system for research in endoscopic telesurgery,” Int. J. Comput. Assist. Radiol. Surg. 5(2), 183193 (2010).CrossRefGoogle ScholarPubMed
Thielmann, S., Seibold, U., Haslinger, R., Passig, G. and Hirzinger, G., “MICA - A New Generation of Versatile Instruments in Robotic Surgery,” IROS 2010, IEEE International Conference on Intelligent Robots and Systems (2010).CrossRefGoogle Scholar
Niu, G., Pan, B., Zhang, F., Feng, H., Gao, W. and Fu, Y., “Dimensional synthesis and concept design of a novel minimally invasive surgical robot,” Robotica 36(5), 715737 (2018).CrossRefGoogle Scholar
Mei, F., Yili, F., Bo, P. and Xudong, Z., “An improved surgical instrument without coupled motions that can be used in robotic-assisted minimally invasive surgery,” Proc. Inst. Mech. Eng. H 226(8), 623630 (2012).CrossRefGoogle ScholarPubMed