Last updated: May 9, 2020 4:00pm
As robotic surgical systems become more and more prominent in hospitals around the world, efficient training in using these systems becomes vital to maximizing the effectiveness of the surgeons and the machines. Our goal with this project is to develop a collateral control system in the AMBF simulator in order to allow for effective surgical training and puzzle completion between two users. Along with developing such a system, a user study will be conducted to test how well these systems fair with real users and surgical experts in instruction and manipulation efficiency.
Robotic surgical systems have become increasingly popular around the world as a tool for surgeons to be able to perform increasingly effective and minimally invasive procedures. Due to this lack of training and access to these machines alternatives for developing the necessary skills for the operation of these machines is crucial for the proliferation of their use, and improvement of their effectiveness as powerful surgical instruments. The aims of this project are:
1. Develop shared control systems for the AMBF -Asynchronous Multibody Framework- simulator (a program capable of simulating virtual environments and tools that are integrable with a dVrk)
2. Develop a new set of puzzles within the AMBF simulator in order to prove the robustness of the simulator as a potential training tool
3. Conduct user study to determine how users most effectively learn how to use the control console with the least amount of frustration and time consumption
The significance of this project is to improve the efficiency of widely distributed surgical training platforms in education and proficiency-building activities. This project is a first step in developing these new systems which could help pave the way for creating new standards in already existing -however not fully standardized- robotic training curricula.
The technical approach for this project is three-fold: development of dual console control schemes, creation of a set of puzzles in AMBF simulator, and the undertaking of a user study to test the effectiveness of these newly developed collateral control systems when compared to traditional learning methodologies. First, collateral control systems will be implemented in the AMBF simulator using C++, which will be added on to already existing, but rudimentary shared control schemes. Second, Blender™ will be used to create 6 new 3D puzzles of varying difficulty (two easy, two medium, two hard) to be then imported into AMBF for use in the user study. Finally, a user study with an estimated size of 30 participants along with 2 experts will be conducted to gather data on user performance after self-teaching versus user performance after collateral control instruction from an expert.
Edit: Due to Covid-19 and class cancellations the user study portion of this project was not completed. Instead all the minimum deliverables were met, which include the dual control system, puzzles and data acquisition script.
Currently unresolved dependencies:
1. Homewood IRB approval to be able to conduct
2. J-Card Access to JHU Robotarium to have access to dVRK
3. Subjects for the user study (Surgeons and trainees)
4. Data collection script for gathering user study data
Satisfied dependencies: 1. Blender software for designing 3D puzzles for the AMBF simulator
2. AMBF Simulator source code for coding collateral control schemes
3. Computer running macOS or Linux for using Blender and coding in C++
4. Repo for puzzles and shared control schemes
Bric, Justin D, et al. “Current State of Virtual Reality Simulation in Robotic Surgery Training: a Review.” Surgical Endoscopy, U.S. National Library of Medicine, June 2016, www.ncbi.nlm.nih.gov/pubmed/26304107.
Bric, Justin, et al. “Proficiency Training on a Virtual Reality Robotic Surgical Skills Curriculum.” Surgical Endoscopy, U.S. National Library of Medicine, Dec. 2014, www.ncbi.nlm.nih.gov/pubmed/24946742.
Lerner, Michelle & Ayalew, Mikias & Peine, William & Sundaram, Chandru. (2010). Does Training on a Virtual Reality Robotic Simulator Improve Performance on the da Vinci (R) Surgical System?. Journal of endourology / Endourological Society. 24. 467-72. 10.1089/end.2009.0190.
Moit, Harley, et al. “A Standardized Robotic Training Curriculum in a General Surgery Program.” JSLS : Journal of the Society of Laparoendoscopic Surgeons, Society of Laparoendoscopic Surgeons, 2019, www.ncbi.nlm.nih.gov/pmc/articles/PMC6924504/.
Sridhar, Ashwin N, et al. “Training in Robotic Surgery-an Overview.” Current Urology Reports, Springer US, Aug. 2017, www.ncbi.nlm.nih.gov/pmc/articles/PMC5486586/.
Here give list of other project files (e.g., source code) associated with the project. If these are online give a link to an appropriate external repository or to uploaded media files under this name space (456-2020-12).
Deliverables Repository: https://github.com/jkawase1/CIIS-ambf
AMBF Simulator Repository: https://github.com/WPI-AIM/ambf