An Introduction to Robotically Assisted Surgical Systems: Current Developments and Focus Areas of Research

Robotic assistance systems for diagnosis and therapy have become technically mature and widely available. Thus, they play an increasingly important role in patient care. This paper provides an overview of the general concepts of robotically assisted surgical systems, briefly revisiting historical and current developments in the surgical robotics market and discussing current focus areas of research. Comprehensiveness cannot be achieved in this format, but besides the general overview, references to further readings and more comprehensive reviews with regard to particular aspects are given. Therefore, the work at hand is considered as an introductory paper into the topic and especially addresses investigators, researchers, medical device manufacturers, and clinicians, who are new to this field. The current research in Robotically Assisted Surgical Systems (RASS) increasingly uses established robotic platforms. To minimize the patient trauma while optimizing the dexterity of the surgeon, miniaturized instruments and semi-autonomous assistance functions are developed. To provide the surgeon with all necessary information in an adequate manner, novel imaging sensors as well as techniques for multimodal sensory feedback and augmented reality are investigated. The Surgical Data Science applies data management and processing approaches including machine learning on medical data to provide optimal, individualized and contextual support to the surgeon. Robotic systems will significantly influence future patient care. Since they must fulfill manifold medical, technical, regulatory and economic requirements, their development calls for a close, active and interdisciplinary cooperation between stakeholders from hospitals, industry and science.

[1]  Brian L. Davies,et al.  Active Constraints/Virtual Fixtures: A Survey , 2014, IEEE Transactions on Robotics.

[2]  Nicolai Schoch,et al.  Surgical Data Science: Enabling Next-Generation Surgery , 2017, ArXiv.

[3]  G. Costamagna,et al.  Robotics and Artificial Intelligence in Gastrointestinal Endoscopy: Updated Review of the Literature and State of the Art , 2021, Current Robotics Reports.

[4]  Gero Strauß,et al.  Research Paper: Validation of Knowledge Acquisition for Surgical Process Models , 2009, J. Am. Medical Informatics Assoc..

[5]  P. Dasgupta,et al.  Future of robotic surgery in urology , 2017, BJU international.

[6]  Nassir Navab,et al.  Surgineering: a new type of collaboration among surgeons and engineers , 2018, International Journal of Computer Assisted Radiology and Surgery.

[7]  Bruno Siciliano,et al.  Modelling and identification of the da Vinci Research Kit robotic arms , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[8]  Guang-Zhong Yang,et al.  From Passive Tool Holders to Microsurgeons: Safer, Smaller, Smarter Surgical Robots , 2014, IEEE Transactions on Biomedical Engineering.

[9]  M. Porter,et al.  Standardizing Patient Outcomes Measurement. , 2016, The New England journal of medicine.

[10]  Peter Kazanzides,et al.  An open-source research kit for the da Vinci® Surgical System , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[11]  Arthur D. Alexander,et al.  Impacts of telemation on modern society , 1972 .

[12]  Andre Esteva,et al.  A guide to deep learning in healthcare , 2019, Nature Medicine.

[13]  J. Dankelman,et al.  Haptics in minimally invasive surgery – a review , 2008, Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy.

[14]  Mamta Mittal,et al.  Big Data and Machine Learning Based Secure Healthcare Framework , 2018 .

[15]  W. Kunert,et al.  Impact of haptic feedback on applied intracorporeal forces using a novel surgical robotic system—a randomized cross-over study with novices in an experimental setup , 2020, Surgical Endoscopy.

[16]  Sebastien Ourselin,et al.  Intraoperative multispectral and hyperspectral label‐free imaging: A systematic review of in vivo clinical studies , 2019, Journal of biophotonics.

[17]  Irfan Halim,et al.  NOTES: The next surgical revolution? , 2008, International journal of surgery.

[18]  G. Buess,et al.  Robotics and systems technology for advanced endoscopic procedures: experiences in general surgery. , 1999, European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery.

[19]  Pierre Jannin,et al.  Surgical process modelling: a review , 2014, International Journal of Computer Assisted Radiology and Surgery.

[20]  I. Frank,et al.  Initial Experience with da Vinci Single-port Robot-assisted Radical Prostatectomies. , 2020, European urology.

[21]  Ewout A. Arkenbout,et al.  Classification of Joints Used in Steerable Instruments for Minimally Invasive Surgery—A Review of the State of the Art , 2015 .

[22]  Vasilis Ntziachristos,et al.  A review of clinical photoacoustic imaging: Current and future trends , 2019, Photoacoustics.

[23]  Paolo Fiorini,et al.  Needle and Biopsy Robots: a Review , 2021, Current Robotics Reports.

[24]  Hyosig Kang,et al.  RIO: Robotic-Arm Interactive Orthopedic System MAKOplasty: User Interactive Haptic Orthopedic Robotics , 2011 .

[25]  J Dankelman,et al.  Scopes Too Flexible...and Too Stiff , 2010, IEEE Pulse.

[26]  Peter Kazanzides,et al.  Software Architecture of the Da Vinci Research Kit , 2017, 2017 First IEEE International Conference on Robotic Computing (IRC).

[27]  Peter Kazanzides,et al.  Architecture of a surgical robot , 1992, [Proceedings] 1992 IEEE International Conference on Systems, Man, and Cybernetics.

[28]  Keno März,et al.  Toward a standard ontology of surgical process models , 2018, International Journal of Computer Assisted Radiology and Surgery.

[29]  Paolo Fiorini,et al.  Current Capabilities and Development Potential in Surgical Robotics , 2015 .

[30]  Robert Haslinger,et al.  A fiberoptic force-torque-sensor for minimally invasive robotic surgery , 2013, 2013 IEEE International Conference on Robotics and Automation.

[31]  David P. Noonan,et al.  Robotic bronchoscopy drive mode of the Auris Monarch platform* , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[33]  Jens-Uwe Stolzenburg,et al.  Current status and future directions of robotic single-site surgery: a systematic review. , 2013, European urology.

[34]  Paolo Fiorini,et al.  Autonomy in Surgical Robotics , 2021, Annu. Rev. Control. Robotics Auton. Syst..

[35]  Olatunji Mumini Omisore,et al.  A Review on Flexible Robotic Systems for Minimally Invasive Surgery , 2022, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[36]  Mamoru Mitsuishi,et al.  Dynamic Active Constraints for Surgical Robots Using Vector-Field Inequalities , 2019, IEEE Transactions on Robotics.

[37]  Brian S. Peters,et al.  Review of emerging surgical robotic technology , 2018, Surgical Endoscopy.

[38]  B L Davies,et al.  Active compliance in robotic surgery—the use of force control as a dynamic constraint , 1997, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[39]  Paolo Fiorini,et al.  Medical Robotics and Computer-Integrated Surgery , 2008, 2008 32nd Annual IEEE International Computer Software and Applications Conference.

[40]  R. Dobbs,et al.  Single-port robotic surgery: the next generation of minimally invasive urology , 2019, World Journal of Urology.

[41]  Bernhard Weber,et al.  The Benefits of Haptic Feedback in Telesurgery and Other Teleoperation Systems: A Meta-Analysis , 2015, HCI.

[42]  Tamas Haidegger,et al.  Autonomy for Surgical Robots: Concepts and Paradigms , 2019, IEEE Transactions on Medical Robotics and Bionics.

[43]  Robert Haslinger,et al.  Fiber optic curvature sensor , 2014, IEEE SENSORS 2014 Proceedings.

[44]  Jacques Marescaux,et al.  Transatlantic robot-assisted telesurgery , 2001, Nature.

[45]  Howie Choset,et al.  Continuum Robots for Medical Applications: A Survey , 2015, IEEE Transactions on Robotics.

[46]  Jindong Liu,et al.  Hands-on reconfigurable robotic surgical instrument holder arm , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[47]  Peter Kazanzides,et al.  Medical robotics—Regulatory, ethical, and legal considerations for increasing levels of autonomy , 2017, Science Robotics.

[48]  R. Dobbs,et al.  Single‐port robot‐assisted laparoscopic radical prostatectomy: initial experience and technique with the da Vinci® SP platform , 2019, BJU international.

[49]  Imre J. Rudas,et al.  Origins of surgical robotics: From space to the operating room , 2016 .

[50]  Gregory D. Hager,et al.  Surgical Data Science - from Concepts to Clinical Translation , 2020, ArXiv.

[51]  Jacques Marescaux,et al.  Enabling single-site laparoscopy: the SPORT platform , 2019, Surgical Endoscopy.

[52]  S. Hayati,et al.  A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery , 1988, IEEE Transactions on Biomedical Engineering.

[53]  Peter Kazanzides,et al.  A Review of Augmented Reality in Robotic-Assisted Surgery , 2020, IEEE Transactions on Medical Robotics and Bionics.

[54]  M. Remacle,et al.  A european multicenter study evaluating the flex robotic system in transoral robotic surgery , 2017, The Laryngoscope.

[55]  Ryan S. Decker,et al.  Supervised autonomous robotic soft tissue surgery , 2016, Science Translational Medicine.

[56]  Huan Liu,et al.  The MUSHA Hand II: A Multi-Functional Hand for Robot-Assisted Laparoscopic Surgery , 2020 .

[57]  Nima Enayati,et al.  Haptics in Robot-Assisted Surgery: Challenges and Benefits , 2016, IEEE Reviews in Biomedical Engineering.

[58]  Elizabeth Warren Strengthening Research through Data Sharing. , 2016, The New England journal of medicine.

[59]  Mamoru Mitsuishi,et al.  Active Constraints Using Vector Field Inequalities for Surgical Robots , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[60]  Blake Hannaford,et al.  Raven-II: An Open Platform for Surgical Robotics Research , 2013, IEEE Transactions on Biomedical Engineering.

[61]  Bruno Siciliano,et al.  A novel force sensing integrated into the trocar for minimally invasive robotic surgery , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[62]  P. Dario,et al.  Frontiers of Robotic Colonoscopy: A Comprehensive Review of Robotic Colonoscopes and Technologies , 2020, Journal of clinical medicine.

[63]  Russell H. Taylor,et al.  Anatomical Mesh-Based Virtual Fixtures for Surgical Robots* , 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[64]  Ronald M. Summers,et al.  A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises , 2020, Proceedings of the IEEE.

[65]  Wolfgang Birkfellner,et al.  Electromagnetic Tracking in Medicine—A Review of Technology, Validation, and Applications , 2014, IEEE Transactions on Medical Imaging.