A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

With robotic-assisted minimally invasive surgery (RAMIS), patients and surgeons benefit from a reduced incision size and dexterous instruments. However, current robotic surgery platforms lack haptic feedback, which is an essential element of safe operation. Moreover, teleportation control challenges make complex surgical tasks like suturing more time-consuming than those that use manual tools. This paper presents a new force-sensing instrument that semi-automates the suturing task and facilitates teleoperated robotic manipulation. In order to generate the ideal needle insertion trajectory and pass the needle through its curvature, the end-effector mechanism has a rotating degree of freedom. Impedance control was used to provide sensory information about needle-tissue interaction forces to the operator using an indirect force estimation approach based on data-based models. The operator's motion commands were then regulated using a hyperplanar virtual fixture (VF) designed to maintain the desired distance between the end-effector and tissue surface while avoiding unwanted contact. To construct the geometry of the VF, an optoelectronic sensor-based approach was developed. Based on the experimental investigation of the hyperplane VF methodology, improved needle-tissue interaction force, manipulation accuracy, and task completion times were demonstrated. Finally, experimental validation of the trained force estimation models and the perceived interaction forces by the user was conducted using online data, demonstrating the potential of the developed approach in improving task performance.

Authors

  • Armin Ehrampoosh
    Robotics and Mechatronics Research Laboratory (RMRL), Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC 3800, Australia.
  • Bijan Shirinzadeh
    Robotics and Mechatronics Research Laboratory (RMRL), Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC 3800, Australia.
  • Joshua Pinskier
    Data61, CSIRO, Brisbane, QLD 4069, Australia.
  • Julian Smith
    Lecturer in Pharmaceutics, University of South Wales, School of Applied Sciences, Pontypridd, CF37 4AT, UK.
  • Randall Moshinsky
    Department of Surgery, Monash University, Melbourne, VIC 3800, Australia.
  • Yongmin Zhong
    School of Engineering, RMIT University, Bundoora, Australia.