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Annual Review of Biomedical Engineering

Volume 21, 2019

Frontiers of Medical Robotics: From Concept to Systems to Clinical Translation

Abstract

Medical robotics is poised to transform all aspects of medicine—from surgical intervention to targeted therapy, rehabilitation, and hospital automation. A key area is the development of robots for minimally invasive interventions. This review provides a detailed analysis of the evolution of interventional robots and discusses how the integration of imaging, sensing, and robotics can influence the patient care pathway toward precision intervention and patient-specific treatment. It outlines how closer coupling of perception, decision, and action can lead to enhanced dexterity, greater precision, and reduced invasiveness. It provides a critical analysis of some of the key interventional robot platforms developed over the years and their relative merit and intrinsic limitations. The review also presents a future outlook for robotic interventions and emerging trends in making them easier to use, lightweight, ergonomic, and intelligent, and thus smarter, safer, and more accessible for clinical use.

Keyword(s): clinical translation, computer-assisted medical intervention, human–robot interaction, medical robotics, minimally invasive surgery, MIS, surgical robots
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/content/journals/10.1146/annurev-bioeng-060418-052502
2019-06-04
2025-04-22
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Literature Cited

  1. 1.
    Kall BA, Kelly PJ, Goerss SJ 1985. Interactive stereotactic surgical system for the removal of intracranial tumors utilizing the CO2 laser and CT-derived database. IEEE Trans. Biomed. Eng. 32:112–16
     [Google Scholar]
  2. 2.
    Kelly PJ, Goerss SJ, Kall BA 1988. Evolution of contemporary instrumentation for computer-assisted stereotactic surgery. Surg. Neurol. 30:204–15
     [Google Scholar]
  3. 3.
    Niaf E, Rouvière O, Mège-Lechevallier F, Bratan F, Lartizien C 2012. Computer-aided diagnosis of prostate cancer in the peripheral zone using multiparametric MRI. Phys. Med. Biol. 57:3833–51
     [Google Scholar]
  4. 4.
    Baumann M, Mozer P, Daanen V, Troccaz J 2012. Prostate biopsy tracking with deformation estimation. Med. Image Anal. 16:562–76
     [Google Scholar]
  5. 5.
    Payan Y 2012. Soft Tissue Biomechanical Modeling for Computer Assisted Surgery Berlin/Heidelberg: Springer
     [Google Scholar]
  6. 6.
    Misra S, Ramesh KT, Okamura AM 2008. Modeling of tool–tissue interactions for computer-based surgical simulation: a literature review. Presence 17:463–91
     [Google Scholar]
  7. 7.
    Huaulmé A, Voros S, Riffaud L, Forestier G, Moreau-Gaudry A, Jannin P 2017. Distinguishing surgical behavior by sequential pattern discovery. J. Biomed. Inform. 67:34–41
     [Google Scholar]
  8. 8.
    Twinanda AP, Shehata S, Mutter D, Marescaux J, de Mathelin M, Padoy N 2017. EndoNet: a deep architecture for recognition tasks on laparoscopic videos. IEEE Trans. Med. Imaging 36:86–97
     [Google Scholar]
  9. 9.
    Beasley RA. 2012. Medical robots: current systems and research directions. J. Robot. 2012:401613
     [Google Scholar]
  10. 10.
    Smith JA, Jivraj J, Wong R, Yang V 2016. 30 years of neurosurgical robots: review and trends for manipulators and associated navigational systems. Ann. Biomed. Eng. 44:836–46
     [Google Scholar]
  11. 11.
    Howe RD, Matsuoka Y. 1999. Robotics for surgery. Annu. Rev. Biomed. Eng. 1:211–40
     [Google Scholar]
  12. 12.
    Dogangil G, Davies BL, Rodriguez y Baena F 2010. A review of medical robotics for minimally invasive soft tissue surgery. Proc. Inst. Mech. Eng. H 224:653–79
     [Google Scholar]
  13. 13.
    Davies B. 2000. A review of robotics in surgery. Proc. Inst. Mech. Eng. H 214:129–40
     [Google Scholar]
  14. 14.
    Taylor RH, Stoianovici D. 2003. Medical robotics in computer-integrated surgery. IEEE Trans. Robot. Autom. 19:765–81
     [Google Scholar]
  15. 15.
    Camarillo DB, Krummel TM, Salisbury JK 2004. Robotic technology in surgery: past, present, and future. Am. J. Surg. 188:4A Suppl.2S–15S
     [Google Scholar]
  16. 16.
    Rebello KJ. 2004. Applications of MEMS in surgery. Proc. IEEE 92:43–55
     [Google Scholar]
  17. 17.
    Menciassi A, Quirini M, Dario P 2007. Microrobotics for future gastrointestinal endoscopy. Minim. Invasive Ther. Allied Technol. 16:91–100
     [Google Scholar]
  18. 18.
    Nelson BJ, Kaliakatsos IK, Abbott JJ 2010. Microrobots for minimally invasive medicine. Annu. Rev. Biomed. Eng. 12:55–85
     [Google Scholar]
  19. 19.
    Ciuti G, Menciassi A, Dario P 2011. Capsule endoscopy: from current achievements to open challenges. IEEE Rev. Biomed. Eng. 4:59–72
     [Google Scholar]
  20. 20.
    Vitiello V, Lee SL, Cundy TP, Yang GZ 2013. Emerging robotic platforms for minimally invasive surgery. IEEE Rev. Biomed. Eng. 6:111–26
     [Google Scholar]
  21. 21.
    Gilbert HB, Rucker DC, Webster RJ III 2016. Concentric tube robots: the state of the art and future directions. Robotics Research M Inaba, P Corke 253–69 Cham, Switz: Springer Int.
     [Google Scholar]
  22. 22.
    Karas CS, Chiocca EA. 2007. Neurosurgical robotics: a review of brain and spine applications. J. Robot. Surg. 1:39–43
     [Google Scholar]
  23. 23.
    Valdastri P, Simi M, Webster RJ 2012. Advanced technologies for gastrointestinal endoscopy. Annu. Rev. Biomed. Eng. 14:397–429
     [Google Scholar]
  24. 24.
    Rafii-Tari H, Payne CJ, Yang G-Z 2014. Current and emerging robot-assisted endovascular catheterization technologies: a review. Ann. Biomed. Eng. 42:697–715
     [Google Scholar]
  25. 25.
    Bergeles C, Vitiello V, Yang G-Z 2016. Surgical robotics: the next 25 years. Successes, challenges, and the road ahead White pap., UK-RAS, Imp. Coll. London London, UK:
     [Google Scholar]
  26. 26.
    Bergeles C, Yang GZ. 2014. From passive tool holders to microsurgeons: safer, smaller, smarter surgical robots. IEEE Trans. Biomed. Eng. 61:1565–76
     [Google Scholar]
  27. 27.
    Kwoh YS, Hou J, Jonckheere EA, Hayati S 1988. A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery. IEEE Trans. Biomed. Eng. 35:153–60
     [Google Scholar]
  28. 28.
    Benabid AL, Cinquin P, Lavalle S, Le Bas JF, Demongeot J, de Rougemont J 1987. Computer-driven robot for stereotactic surgery connected to CT scan and magnetic resonance imaging. Stereotact. Funct. Neurosurg. 50:153–54
     [Google Scholar]
  29. 29.
    Lavallee S, Troccaz J, Gaborit L, Cinquin P, Benabid AL, Hoffmann D 1992. Image guided operating robot: a clinical application in stereotactic neurosurgery. Proceedings of the 1992 IEEE International Conference on Robotics and Automation618–24 Piscataway, NJ: IEEE
     [Google Scholar]
  30. 30.
    Li QH, Zamorano L, Pandya A, Perez R, Gong J, Diaz F 2002. The application accuracy of the NeuroMate robot—a quantitative comparison with frameless and frame-based surgical localization systems. Comput. Aided Surg. 7:90–98
     [Google Scholar]
  31. 31.
    Schweikard A, Shiomi H, Adler J 2004. Respiration tracking in radiosurgery. Med. Phys. 31:2738–41
     [Google Scholar]
  32. 32.
    Bertelsen A, Melo J, Sánchez E, Borro D 2013. A review of surgical robots for spinal interventions. Int. J. Med. Robot. 9:407–22
     [Google Scholar]
  33. 33.
    Dahroug B, Tamadazte B, Tavernier L, Weber S, Andreff N 2018. Review on otological robotic systems: toward micro-robot assisted cholesteatoma surgery. IEEE Rev. Biomed. Eng. 11:125–42
     [Google Scholar]
  34. 34.
    Weber S, Gavaghan K, Wimmer W, Williamson T, Gerber N et al. 2017. Instrument flight to the inner ear. Sci. Robot. 2:eaal4916
     [Google Scholar]
  35. 35.
    Tavernier L, Andreff N, Fujimoto T, Peretti G, Mattos L 2017. Micro-technologies and systems for robot-assisted laser phonomicrosurgery (μRALP). Robotics and Digital Guidance in ENT–H&N Surgery B Lombard, P Céruse 142–53 Amsterdam: Elsevier
     [Google Scholar]
  36. 36.
    Mattos LS, Caldwell DG, Peretti G, Mora F, Guastini L, Cingolani R 2016. Microsurgery robots: addressing the needs of high-precision surgical interventions. Swiss Med. Wkly. 146:w14375
     [Google Scholar]
  37. 37.
    Dagnino G, Mattos LS, Caldwell DG 2015. A vision-based system for fast and accurate laser scanning in robot-assisted phonomicrosurgery. Int. J. Comput. Assist. Radiol. Surg. 10:217–29
     [Google Scholar]
  38. 38.
    Paul HA, Mittlestadt B, Bargar WL, Musits B, Taylor RH et al. 1992. A surgical robot for total hip replacement surgery. Proceedings of the 1992 IEEE International Conference on Robotics and Automation606–11 Piscataway, NJ: IEEE
     [Google Scholar]
  39. 39.
    Taylor RH, Mittelstadt BD, Paul HA, Hanson W, Kazanzides P et al. 1994. An image-directed robotic system for precise orthopaedic surgery. IEEE Trans. Robot. Autom. 10:261–75
     [Google Scholar]
  40. 40.
    Paul HA, Bargar WL, Mittlestadt B, Musits B, Taylor RH et al. 1992. Development of a surgical robot for cementless total hip arthroplasty. Clin. Orthop. Relat. Res. 285:57–66
     [Google Scholar]
  41. 41.
    Jakopec M, Harris SJ, Gomes P, Cobb J, Davies BL 2003. The hands-on orthopaedic robot “Acrobot”: early clinical trials of total knee replacement surgery. Robot. Autom. IEEE Trans. 19:902–11
     [Google Scholar]
  42. 42.
    Troccaz J, Peshkin M, Davies B 1998. Guiding systems for computer-assisted surgery: introducing synergistic devices and discussing the different approaches. Med. Image Anal. 2:101–19
     [Google Scholar]
  43. 43.
    Rosenberg LB. 1993. Virtual fixtures: perceptual tools for telerobotic manipulation. Proceedings of IEEE Virtual Reality Annual International Symposium76–82 Piscataway, NJ: IEEE
     [Google Scholar]
  44. 44.
    Bowyer SA, Davies BL, Rodriguez y Baena F 2014. Active constraints/virtual fixtures: a survey. IEEE Trans. Robot. 30:138–57
     [Google Scholar]
  45. 45.
    Schneider O, Troccaz J. 2001. A six-degree-of-freedom passive arm with dynamic constraints (PADyC) for cardiac surgery application: preliminary experiments. Comput. Aided Surg. 6:340–51
     [Google Scholar]
  46. 46.
    Lang JE, Mannava S, Floyd AJ, Goddard MS, Smith BP et al. 2011. Robotic systems in orthopaedic surgery. Bone Jt. J. 93B:1296–99
     [Google Scholar]
  47. 47.
    Herry Y, Batailler C, Lording T, Servien E, Neyret P, Lustig S 2017. Improved joint-line restitution in unicompartmental knee arthroplasty using a robotic-assisted surgical technique. Int. Orthop. 41:2265–71
     [Google Scholar]
  48. 48.
    Lonner JH, Smith JR, Picard F, Hamlin B, Rowe PJ, Riches PE 2015. High degree of accuracy of a novel image-free handheld robot for unicondylar knee arthroplasty in a cadaveric study. Clin. Orthop. Relat. Res. 473:206–12
     [Google Scholar]
  49. 49.
    Plaskos C, Cinquin P, Lavallée S, Hodgson AJ 2005. Praxiteles: a miniature bone-mounted robot for minimal access total knee arthroplasty. Int. J. Med. Robot. Comput. Assist. Surg. 1:67–79
     [Google Scholar]
  50. 50.
    Koulalis D, O'Loughlin PF, Plaskos C, Kendoff D, Cross MB, Pearle AD 2011. Sequential versus automated cutting guides in computer-assisted total knee arthroplasty. Knee 18:436–42
     [Google Scholar]
  51. 51.
    Lieberman IH, Togawa D, Kayanja MM, Reinhardt MK, Friedlander A et al. 2006. Bone-mounted miniature robotic guidance for pedicle screw and translaminar facet screw placement. Part I. Technical development and a test case result. Neurosurgery 59:641–50
     [Google Scholar]
  52. 52.
    Togawa D, Kayanja MM, Reinhardt MK, Shoham M, Balter A et al. 2007. Bone-mounted miniature robotic guidance for pedicle screw and translaminar facet screw placement. Part 2. Evaluation of system accuracy. Neurosurgery 60:Suppl. 1129–39
     [Google Scholar]
  53. 53.
    Shoham M, Lieberman IH, Benzel EC, Togawa D, Zehavi E et al. 2007. Robotic assisted spinal surgery—from concept to clinical practice. Comput. Aided Surg. 12:105–15
     [Google Scholar]
  54. 54.
    Troccaz J 2012. Medical Robotics London: ISTE
     [Google Scholar]
  55. 55.
    Gonzales AV, Cinquin P, Troccaz J, Guerraz A, Hennion B et al. 2001. TER: a system for robotic tele-echography. Proceedings of the 2001 International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2001)326–34 Berlin: Springer
     [Google Scholar]
  56. 56.
    Vilchis A, Troccaz J, Cinquin P, Masuda K, Pellissier F 2003. A new robot architecture for tele-echography. IEEE Trans. Robot. Autom. 19:922–26
     [Google Scholar]
  57. 57.
    Martinelli T, Bosson J-L, Bressollette L, Pelissier F, Boidard E et al. 2007. Robot-based tele-echography: clinical evaluation of the TER system in abdominal aortic exploration. J. Ultrasound Med. 26:1611–16
     [Google Scholar]
  58. 58.
    Hu X, Ohnmeiss DD, Lieberman IH 2013. Robotic-assisted pedicle screw placement: lessons learned from the first 102 patients. Eur. Spine J. 22:661–66
     [Google Scholar]
  59. 59.
    Fiani B, Quadri SA, Farooqui M, Cathel A, Berman B et al. 2018. Impact of robot-assisted spine surgery on health care quality and neurosurgical economics: a systemic review. Neurosurg. Rev https://doi.org/10.1007/s10143-018-0971-z
     [Google Scholar]
  60. 60.
    Buschbaum J, Fremd R, Pohlemann T, Kristen A 2014. Computer-assisted fracture reduction: a new approach for repositioning femoral fractures and planning reduction paths. Int. J. Comput. Assist. Radiol. Surg. 10:149–59
     [Google Scholar]
  61. 61.
    Joskowicz L, Milgrom C, Simkin A, Tockus L, Yaniv Z 1998. FRACAS: a system for computer-aided image–guided long bone fracture surgery. Comput. Aided Surg. 3:271–88
     [Google Scholar]
  62. 62.
    Warisawa S, Ishizuka T, Mitsuishi M, Sugano N 2004. Development of a femur fracture reduction robot. Proceedings of the 2004 IEEE International Conference on Robotics and Automation3999–4004 Piscataway, NJ: IEEE
     [Google Scholar]
  63. 63.
    Westphal R, Winkelbach S, Wahl F, Gösling T, Oszwald M et al. 2009. Robot-assisted long bone fracture reduction. Int. J. Robot. Res. 28:1259–78
     [Google Scholar]
  64. 64.
    Tang P, Hu L, Du H, Gong M, Zhang L 2012. Novel 3D hexapod computer-assisted orthopaedic surgery system for closed diaphyseal fracture reduction. Int. J. Med. Robot. 8:17–24
     [Google Scholar]
  65. 65.
    Graham AE, Xie SQ, Aw KC, Xu WL, Mukherjee S 2006. Design of a parallel long bone fracture reduction robot with planning treatment tool. Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems1255–60 Piscataway, NJ: IEEE
     [Google Scholar]
  66. 66.
    Wang J, Han W, Lin H 2013. Femoral fracture reduction with a parallel manipulator robot on a traction table. Int. J. Med. Robot. Comput. Assist. Surg. 9:464–71
     [Google Scholar]
  67. 67.
    Dagnino G, Georgilas I, Köhler P, Atkins R, Dogramadzi S 2016. Image-based robotic system for enhanced minimally invasive intra-articular fracture surgeries. . Proceedings of the 2016 IEEE International Conference on Robotics and Automation696–701 Piscataway, NJ: IEEE
     [Google Scholar]
  68. 68.
    Dagnino G, Georgilas I, Köhler P, Morad S, Atkins R, Dogramadzi S 2016. Navigation system for robot-assisted intra-articular lower-limb fracture surgery. Int. J. Comput. Assist. Radiol. Surg. 11:1831–43
     [Google Scholar]
  69. 69.
    Dagnino G, Georgilas I, Morad S, Gibbons P, Tarassoli P et al. 2017. Image-guided surgical robotic system for percutaneous reduction of joint fractures. Ann. Biomed. Eng. 45:2648–62
     [Google Scholar]
  70. 70.
    Georgilas I, Dagnino G, Tarassoli P, Atkins R, Dogramadzi S 2018. Robot-assisted fracture surgery: surgical requirements and system design. Ann. Biomed. Eng. 46:1637–49
     [Google Scholar]
  71. 71.
    Kraft BM, Jäger C, Kraft K, Leibl BJ, Bittner R 2004. The AESOP robot system in laparoscopic surgery: increased risk or advantage for surgeon and patient. ? Surg. Endosc. Interv. Tech. 18:1216–23
     [Google Scholar]
  72. 72.
    Taylor RH, Funda J, Eldridge B, Gomory S, Gruben K et al. 1995. A telerobotic assistant for laparoscopic surgery. IEEE Eng. Med. Biol. 14:279–88
     [Google Scholar]
  73. 73.
    Finlay PA, Ornstein MH. 1995. Controlling the movement of a surgical laparoscope. IEEE Eng. Med. Biol. 14:289–91
     [Google Scholar]
  74. 74.
    Berkelman P, Cinquin P, Boidard E, Troccaz J, Létoublon C, Ayoubi J-M 2003. Design, control and testing of a novel compact laparoscopic endoscope manipulator. Proc. Inst. Mech. Eng. I. 217329–41
  75. 75.
    Voros S, Haber GP, Menudet JF, Long JA, Cinquin P 2010. Viky robotic scope holder: initial clinical experience and preliminary results using instrument tracking. IEEE ASME Trans. Mechatron. 15:879–86
     [Google Scholar]
  76. 76.
    Ng WS, Davies BL, Hibberd RD, Timoney AG 1993. Robotic surgery: a first-hand experience in transurethral resection of the prostate. IEEE Eng. Med. Biol. 12:120–25
     [Google Scholar]
  77. 77.
    Harris SJ, Arambula-Cosio F, Mei Q, Hibberd RD, Davies BL et al. 1997. The Probot—an active robot for prostate resection. Proc. Inst. Mech. Eng. H 211:317–25
     [Google Scholar]
  78. 78.
    Butner SE, Ghodoussi M. 2003. Transforming a surgical robot for human telesurgery. IEEE Trans. Robot. Autom. 19:818–24
     [Google Scholar]
  79. 79.
    Marescaux J, Leroy J, Gagner M, Rubino F, Mutter D et al. 2001. Transatlantic robot-assisted telesurgery. Nature 413:379–80
     [Google Scholar]
  80. 80.
    Guthart GS, Salisbury JK. 2000. The Intuitive telesurgery system: overview and application. Proceedings of the 2000 IEEE International Conference on Robotics and Automation618–21 Piscataway, NJ: IEEE
     [Google Scholar]
  81. 81.
    Yaxley JW, Coughlin GD, Chambers SK, Occhipinti S, Samaratunga H et al. 2016. Robot-assisted laparoscopic prostatectomy versus open radical retropubic prostatectomy: early outcomes from a randomised controlled phase 3 study. Lancet 388:1057–66
     [Google Scholar]
  82. 82.
    Pacchierotti C. 2015. Cutaneous Haptic Feedback in Robotic Teleoperation Cham, Switz: Springer Int.
     [Google Scholar]
  83. 83.
    Ota T, Degani A, Schwartzman D, Zubiate B, McGarvey J et al. 2009. A highly articulated robotic surgical system for minimally invasive surgery. Ann. Thorac. Surg. 87:1253–56
     [Google Scholar]
  84. 84.
    Lang S, Mattheis S, Hasskamp P, Lawson G, Güldner C et al. 2017. A European multicenter study evaluating the flex robotic system in transoral robotic surgery. Laryngoscope 127:391–95
     [Google Scholar]
  85. 85.
    Shang J, Noonan DP, Payne C, Clark J, Sodergren MH et al. 2011. An articulated universal joint based flexible access robot for minimally invasive surgery. Proceedings of the 2011 IEEE International Conference on Robotics and Automation1147–52 Piscataway, NJ: IEEE
     [Google Scholar]
  86. 86.
    Newton RC, Noonan DP, Vitiello V, Clark J, Payne CJ et al. 2012. Robot-assisted transvaginal peritoneoscopy using confocal endomicroscopy: a feasibility study in a porcine model. Surg. Endosc. 26:2532–40
     [Google Scholar]
  87. 87.
    Di Marco AN, Jeyakumar J, Pratt PJ, Yang G-Z, Darzi AW 2016. Evaluating a novel 3D stereoscopic visual display for transanal endoscopic surgery: a randomized controlled crossover study. Ann. Surg. 263:36–42
     [Google Scholar]
  88. 88.
    Shang J, Leibrandt K, Giataganas P, Vitiello V, Seneci CA et al. 2017. A single-port robotic system for transanal microsurgery—design and validation. IEEE Robot. Autom. Lett. 2:1510–17
     [Google Scholar]
  89. 89.
    Lee S-L, Constantinescu M, Chi W, Yang G-Z 2017. Devices for endovascular interventions: technical advances and translational challenges White pap., Natl. Inst. Health Res./Clin. Res. Netw London, UK:
     [Google Scholar]
  90. 90.
    Walker TG, Kalva SP, Yeddula K, Wicky S, Kundu S et al. 2010. Clinical practice guidelines for endovascular abdominal aortic aneurysm repair: written by the Standards of Practice Committee for the Society of Interventional Radiology and endorsed by the Cardiovascular and Interventional Radiological Society of Europe and the Canadian Interventional Radiology Association. J. Vasc. Interv. Radiol. 21:1632–55
     [Google Scholar]
  91. 91.
    Di Biase L, Wang Y, Horton R, Gallinghouse GJ, Mohanty P et al. 2009. Ablation of atrial fibrillation utilizing robotic catheter navigation in comparison to manual navigation and ablation: single-center experience. J. Cardiovasc. Electrophysiol. 20:1328–35
     [Google Scholar]
  92. 92.
    Riga CV, Bicknell CD, Rolls A, Cheshire NJ, Hamady MS 2013. Robot-assisted fenestrated endovascular aneurysm repair (FEVAR) using the Magellan system. J. Vasc. Interv. Radiol. 24:191–96
     [Google Scholar]
  93. 93.
    Feng Y, Guo Z, Dong Z, Zhou X-Y, Kwok K-W et al. 2017. An efficient cardiac mapping strategy for radiofrequency catheter ablation with active learning. Int. J. Comput. Assist. Radiol. Surg. 12:1199–207
     [Google Scholar]
  94. 94.
    Cordemans V, Kaminski L, Banse X, Francq BG, Cartiaux O 2017. Accuracy of a new intraoperative cone beam CT imaging technique (Artis zeego II) compared to postoperative CT scan for assessment of pedicle screws placement and breaches detection. Eur. Spine J. 26:2906–16
     [Google Scholar]
  95. 95.
    Sears P, Dupont P. 2006. A steerable needle technology using curved concentric tubes. Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems2850–56 Piscataway, NJ: IEEE
     [Google Scholar]
  96. 96.
    Webster RJ. 2007. Design and mechanics of continuum robots for surgery PhD thesis, Johns Hopkins Univ Baltimore, MD:
     [Google Scholar]
  97. 97.
    Furusho J, Ono T, Murai R, Fujimoto T, Chiba Y, Horio H 2005. Development of a curved multi-tube (CMT) catheter for percutaneous umbilical blood sampling and control methods of CMT catheters for solid organs. Proceedings of the 2005 IEEE International Conference Mechatronics and Automation410–15 Piscataway, NJ: IEEE
     [Google Scholar]
  98. 98.
    Dupont PE, Lock J, Itkowitz B, Butler E 2010. Design and control of concentric-tube robots. IEEE Trans. Robot. 26:209–25
     [Google Scholar]
  99. 99.
    Webster RJ III, Swensen JP, Romano JM, Cowan NJ 2009. Closed-form differential kinematics for concentric-tube continuum robots with application to visual servoing. Experimental Robotics O Khatib, V Kumar, GJ Pappas 485–94 Berlin/Heidelberg: Springer
     [Google Scholar]
  100. 100.
    Arabagi V, Gosline A, Wood RJ, Dupont PE 2013. Simultaneous soft sensing of tissue contact angle and force for millimeter-scale medical robots. Proceedings of the 2013 IEEE International Conference on Robotics and Automation4396–402 Piscataway, NJ: IEEE
     [Google Scholar]
  101. 101.
    Burgner J, Rucker DC, Gilbert HB, Swaney PJ, Russell PT et al. 2014. A telerobotic system for transnasal surgery. IEEE ASME Trans. Mechatron. 19:996–1006
     [Google Scholar]
  102. 102.
    Gosline AH, Vasilyev NV, Butler EJ, Folk C, Cohen A et al. 2012. Percutaneous intracardiac beating-heart surgery using metal MEMS tissue approximation tools. Int. J. Robot. Res. 31:1081–93
     [Google Scholar]
  103. 103.
    Swaney PJ, Croom JM, Burgner J, Gilbert HB, Rucker DC et al. 2012. Design of a quadramanual robot for single-nostril skull base surgery. Proceedings of the 5th Annual Dynamic Systems and Control Conference/11th Motion and Vibration Conference387–93 New York: ASME
     [Google Scholar]
  104. 104.
    Estape R. 2018. Early acute in-vivo experience in gynecology oncology applications with the SPORT surgical system technology White pap., Titan Medical Inc Toronto, Can:.
     [Google Scholar]
  105. 105.
    Iddan G, Meron G, Glukhovsky A, Swain P 2000. Wireless capsule endoscopy. Nature 405:417
     [Google Scholar]
  106. 106.
    Spada C, Spera G, Riccioni M, Biancone L, Petruzziello L et al. 2005. A novel diagnostic tool for detecting functional patency of the small bowel: the Given patency capsule. Endoscopy 37:793–800
     [Google Scholar]
  107. 107.
    Gorini S, Quirini M, Menciassi A, Pernorio G, Stefanini C, Dario P 2006. A novel SMA-based actuator for a legged endoscopic capsule. Proceedings of the 1st IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics443–49 Piscataway, NJ: IEEE
     [Google Scholar]
  108. 108.
    Kwon J, Park S, Park J, Kim B 2007. Evaluation of the critical stroke of an earthworm-like robot for capsule endoscopes. Proc. Inst. Mech. Eng. H 221:397–405
     [Google Scholar]
  109. 109.
    Ciuti G, Valdastri P, Menciassi A, Dario P 2010. Robotic magnetic steering and locomotion of capsule endoscope for diagnostic and surgical endoluminal procedures. Robotica 28:199–207
     [Google Scholar]
  110. 110.
    Ciuti G, Donlin R, Valdastri P, Arezzo A, Menciassi A et al. 2010. Robotic versus manual control in magnetic steering of an endoscopic capsule. Endoscopy 42:148–52
     [Google Scholar]
  111. 111.
    Rey J-F, Ogata H, Hosoe N, Ohtsuka K, Ogata N et al. 2012. Blinded nonrandomized comparative study of gastric examination with a magnetically guided capsule endoscope and standard videoendoscope. Gastrointest. Endosc. 75:373–81
     [Google Scholar]
  112. 112.
    Popek KM, Hermans T, Abbott JJ 2017. First demonstration of simultaneous localization and propulsion of a magnetic capsule in a lumen using a single rotating magnet. Proceedings of the 2017 IEEE International Conference on Robotics and Automation1154–60 Piscataway, NJ: IEEE
     [Google Scholar]
  113. 113.
    Kong K, Cha J, Jeon D, Cho DD 2005. A rotational micro biopsy device for the capsule endoscope. Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems1839–43 Piscataway, NJ: IEEE
     [Google Scholar]
  114. 114.
    Simi M, Gerboni G, Menciassi A, Valdastri P 2012. Magnetic mechanism for wireless capsule biopsy. J. Med. Devices 6:017611
     [Google Scholar]
  115. 115.
    Payne CJ, Yang G-Z. 2014. Hand-held medical robots. Ann. Biomed. Eng. 42:1594–605
     [Google Scholar]
  116. 116.
    Payne CJ, Rafii-Tari H, Yang GZ 2012. A force feedback system for endovascular catheterisation. Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems1298–304 Piscataway, NJ: IEEE
     [Google Scholar]
  117. 117.
    Li J, de Ávila BE-F, Gao W, Zhang L, Wang J 2017. Micro/nanorobots for biomedicine: delivery, surgery, sensing, and detoxification. Sci. Robot. 2:eaam6431
     [Google Scholar]
  118. 118.
    Zebda A, Alcaraz J-P, Vadgama P, Shleev S, Minteer SD et al. 2018. Challenges for successful implantation of biofuel cells. Bioelectrochemistry 124:57–72
     [Google Scholar]
  119. 119.
    Ghelfi J, Moreau-Gaudry A, Hungr N, Fouard C, Véron B et al. 2018. Evaluation of the needle positioning accuracy of a light puncture robot under MRI guidance: results of a clinical trial on healthy volunteers. Cardiovasc. Intervent. Radiol. 41:1428–35
     [Google Scholar]
  120. 120.
    Yang G-Z, Bellingham J, Dupont PE, Fischer P, Floridi L et al. 2018. The grand challenges of science robotics. Sci. Robot. 3:eaar7650
     [Google Scholar]
  121. 121.
    Rafii-Tari H, Liu J, Lee S-L, Bicknell C, Yang G-Z 2013. Learning-based modeling of endovascular navigation for collaborative robotic catheterization. Med. Image Comput. 16:369–77
     [Google Scholar]
  122. 122.
    Yang G-Z, Cambias J, Cleary K, Daimler E, Drake J et al. 2017. Medical robotics—regulatory, ethical, and legal considerations for increasing levels of autonomy. Sci. Robot. 2:eaam8638
     [Google Scholar]
  123. 123.
    Bargar WL, Bauer A, Börner M 1998. Primary and revision total hip replacement using the Robodoc system. Clin. Orthop. Relat. Res. 354:82–91
     [Google Scholar]
  124. 124.
    Marcus HJ, Payne CJ, Hughes-Hallett A, Gras G, Leibrandt K et al. 2016. Making the leap: the translation of innovative surgical devices from the laboratory to the operating room. Ann. Surg. 263:1077–78
     [Google Scholar]
  125. 125.
    Marcus HJ, Payne CJ, Hughes-Hallett A, Marcus AP, Yang G-Z et al. 2016. Regulatory approval of new medical devices: cross sectional study. BMJ 353:i2587
     [Google Scholar]
  126. 126.
    Jeong IG, Khandwala YS, Kim JH, Han DH, Li S et al. 2017. Association of robotic-assisted versus laparoscopic radical nephrectomy with perioperative outcomes and health care costs, 2003 to 2015. JAMA 318:1561–68
     [Google Scholar]
  127. 127.
    Jayne D, Pigazzi A, Marshall H, Croft J, Corrigan N et al. 2017. Effect of robotic-assisted versus conventional laparoscopic surgery on risk of conversion to open laparotomy among patients undergoing resection for rectal cancer: the ROLARR randomized clinical trial. JAMA 318:1569–80
     [Google Scholar]
  128. 128.
    Wright JD. 2017. Robotic-assisted surgery: balancing evidence and implementation. JAMA 318:1545–47
     [Google Scholar]
  129. 129.
    Keel G, Savage C, Rafiq M, Mazzocato P 2017. Time-driven activity-based costing in health care: a systematic review of the literature. Health Policy 121:755–63
     [Google Scholar]
  130. 130.
    Liow MHL, Chin PL, Pang HN, Tay DK-J, Yeo S-J 2017. THINK surgical TSolution-One® (Robodoc) total knee arthroplasty. SICOT J 3:63
     [Google Scholar]
  131. 131.
    Shenoy R, Nathwani D. 2017. Evidence for robots. SICOT J 3:38
     [Google Scholar]
  132. 132.
    Troccaz J, Berkelman P, Cinquin P, Vilchis-Gonzales A 2002. Interactive robots for medical applications. Proceedings of the 6th Annual Conference of the International Society for Computer Aided Surgery (CARS 2002)175–80 Berlin/Heidelberg: Springer
     [Google Scholar]
  133. 133.
    Hungr N, Baumann M, Long J, Troccaz J 2012. A 3-D ultrasound robotic prostate brachytherapy system with prostate motion tracking. IEEE Trans. Robot. 28:1382–97
     [Google Scholar]
  134. 134.
    Long J-A, Hungr N, Baumann M, Descotes J-L, Bolla M et al. 2012. Development of a novel robot for transperineal needle based interventions: focal therapy, brachytherapy and prostate biopsies. J. Urol. 188:1369–74
     [Google Scholar]
  135. 135.
    Veron B, Hungr N, Troccaz J 2016. Making a clinical device from a laboratory prototype: from Prosper to Prosper OR. Proceedings of the 6th Joint Workshop on New Technologies for Computer/Robot Assisted Surgery http://hal.univ-grenoble-alpes.fr/hal-01455696/document
    [Google Scholar]
  136. 136.
    Research and Markets Ltd. 2018. Medical robots market to 2025—global analysis and forecasts by product; application, end-user and geography Report 4617877, Research and Markets Ltd Dublin, Irel: https://www.researchandmarkets.com/reports/4617877/medical-robots-market-to-2025-global-analysis
    [Google Scholar]
  137. 137.
    Intuitive Surgical 2016. Annual Report 2016 Report, Intuitive Surgical Sunnyvale, CA: http://www.annualreports.com/HostedData/AnnualReportArchive/i/NASDAQ_ISRG_2016.pdf
    [Google Scholar]
  138. 138.
    Köckerling F. 2014. Robotic vs. standard laparoscopic technique—what is better?. Front. Surg. 1:15
     [Google Scholar]
  139. 139.
    Baek SJ, Kim SH. 2014. Robotics in general surgery: an evidence-based review. Asian J. Endosc. Surg. 7:117–23
     [Google Scholar]
  140. 140.
    Grimsby GM, Dwyer ME, Jacobs MA, Ost MC, Schneck FX et al. 2015. Multi-institutional review of outcomes of robot-assisted laparoscopic extravesical ureteral reimplantation. J. Urol. 193:1791–95
     [Google Scholar]
  141. 141.
    Hughes D, Camp C, O'Hara J, Adshead J 2016. Health resource use after robot-assisted surgery vs open and conventional laparoscopic techniques in oncology: analysis of English secondary care data for radical prostatectomy and partial nephrectomy. BJU Int 117:940–47
     [Google Scholar]
  142. 142.
    Keel G, Savage C, Rafiq M, Mazzoccato P 2017. Time-driven activity-based costing in health care: a systematic review of the literature. Health Policy 121:755–63
     [Google Scholar]
  143. 143.
    Jeong IG, Khandwala YS, Kim JH, Han DH, Li S et al. 2017. Association of robotic-assisted vs laparoscopic radical nephrectomy with perioperative outcomes and health care costs, 2003 to 2015. JAMA 318:1561–68
     [Google Scholar]
  144. 144.
    Childers CP, Maggard-Gibbons M. 2018. Estimation of the acquisition and operating costs for robotic surgery. JAMA 320:835–36
     [Google Scholar]
  145. 145.
    Kosugi Y, Watanabe E, Goto J, Watanabe T, Yoshimoto S et al. 1988. An articulated neurosurgical navigation system using MRI and CT images. IEEE Trans. Biomed. Eng. 35:147–52
     [Google Scholar]
/content/journals/10.1146/annurev-bioeng-060418-052502
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Frontiers of Medical Robotics: From Concept to Systems to Clinical Translation
Annual Review of Biomedical Engineering 21, 193 (2019); https://doi.org/10.1146/annurev-bioeng-060418-052502
/content/journals/10.1146/annurev-bioeng-060418-052502
/content/journals/10.1146/annurev-bioeng-060418-052502
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