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Implementation and evaluation of an arthroscopic tracker system for intraoperative motion tracking and force registration

• Oystein Bjelland
• Lars Ivar Hatledal
• Martin Steinert
• Robin T. Bye

(2023). ECMS 2023, 37th Proceedings
Edited by: Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni, European Council for Modelling and Simulation.
DOI: http://doi.org/10.7148/2023
ISSN: 2522-2422 (ONLINE)
ISSN: 2522-2414 (PRINT)
ISSN: 2522-2430 (CD-ROM)
ISBN: 978-3-937436-80-7
ISBN: 978-3-937436-79-1 (CD) Communications of the ECMS Volume 37, Issue 1, June 2023, Florence, Italy June 20th – June 23rd, 2023

https://doi.org/10.7148/2023-0459

Oystein bjelland, Lars ivar hatledal, Martin steinert, Robin t. bye (2023). Implementation and Evaluation of an Arthroscopic Tracker System for Intraoperative Motion Tracking and Force Registration, ECMS 2023, Proceedings Edited by: Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni, European Council for Modelling and Simulation. doi:10.7148/2023-0459

This paper presents implementation and evaluation of an intraoperative arthroscopic tracker system for research and educational use. The system enables automatic pose and force data exchange between a physical asset and a digital model, which is required in arthroscopic digital twins. Surgical instrument motion tracking is captured using an inertial measurement unit in combination with stereo vision (ZED mini, Stereolabs, USA), and force registration is achieved using a 6 degree-of-freedom force-torque sensor (Nano 25, ATI Industrial Automation, USA). An integration layer in the software system continuously fetches data from the sensors, and transmits data over a network connection. The software visualization layer displays the instrument pose and force readings relative to a 3D anatomical model in real-time (24 Hz). Position accuracy of the system was compared to a Kuka LBR Med 14 R820 collaborative robot, and the total root mean square error was found to be 12.60 mm. A post-operative instrument trajectory map from sampled pose and force/torque data was implemented in Matlab, and demonstrated in an experiment. The system is feasible for use in many research and educational applications.