Smart tools: These are instrumented surgical tools which enable quantitative techniques in the operating room.
Surgical Robotics: This includes custom built robots that automate access to all patient surgical sites and the operating room environment, extracting meaningful information such as procedural markers or surgical skill from the sensor streams of the robot, and creating new algorithms and tools that enable novel surgical procedures.
Surgical Simulation: In collaboration with the center for research in education and surgical training (CREST), we investigate novel techniques for training surgical procedures in virtual reality or realistic mock tissues.
Surgical Genome Project: In collaboration with the University of Washington, this project aims to create a large, open database of surgical procedures including tool tracking, operative video, and a variety of sensors inputs. The aim is to provide a common resource for researchers to investigate surgical behavior, design requirements, and to develop and compare analysis algorithms in a repeatable way.
John O'Neill, Jason Lu, Rodney Dockter, and Timothy Kowalewski. Stretchable, flexible, scalable smart skin sensors for robotic position and force estimation. Sensors, 18(4):953, 2018.
John J O'Neill, Trevor K Stephens, and Timothy M Kowalewski. Evaluation of torque measurement surrogates as applied to grip torque and jaw angle estimation of robotic surgical tools. IEEE Robotics and Automation Letters, 3(4):3027--3034, 2018.
Trevor K Stephens, Nathan J Kong, Rodney L Dockter, John J O'Neill, Robert M Sweet, and Timothy M Kowalewski. Blended shared control utilizing online identification. International Journal of Computer Assisted Radiology and Surgery, 13(6):769--776, 2018.
Trevor K Stephens, John J O'Neill, Nathan J Kong, Mark V Mazzeo, Jack E Norfleet, Robert M Sweet, and Timothy M Kowalewski. Conditions for reliable grip force and jaw angle estimation of da vinci surgical tools. International journal of computer assisted radiology and surgery, pages 1--11, 2018.
Rodney L. Dockter, Thomas S. Lendvay, Robert M. Sweet, and Timothy M. Kowalewski. The minimally acceptable classification criterion for surgical skill: Intent vectors and separability of raw motion data. International Journal of Computer Assisted Radiology and Surgery, 12(7):1151--1159, July 2017.