Unmet Need:
Current techniques in medical robotics rely solely on surgeon-controlled robots, resulting in an error rate of as high as 22% primarily from user error. Automation has become the standard across many industries; however, due to the uncertainty and irregularities of surgical procedures, automation has not become a suitable option. Introducing surgeon supervised automation into medical robotics can help to lower this error rate by lowering the responsibilities of the surgeon during the procedure to fine controls during the procedure. This can be achieved via a dynamic interaction with the human user and informing them about the control modes in next steps of surgery. This leaves a need for a surgical system which can leverage the repeatability of automation with the fine skills of surgeons.
Technology Overview
Researchers at Johns Hopkins University have developed a supervised-autonomous platform for automatic suturing within surgical procedures. This platform is capable of fully autonomous suture placement with an accuracy of 85.4% and supervised placement at an accuracy of 98.1%, as well as 1.6 times better consistency in suture spacing and 1.8 times better consistency in suture bite sizes than the manual results.
Stage of Development
The system has been fully prototyped and is entering the preclinical stage of testing.
Publications
M. Kam, H. Saeidi, M. H. Hsieh, J. U. Kang, and A. Krieger, "A Confidence-Based Supervised-Autonomous Control Strategy for Robotic Vaginal Cuff Closure," in 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021.
