Visualization Tool For Robotic/Universal Force-Moment Sensor Experiments
John Jolly, Richard Debski Ph.D., Eric Wong B.S.

Musculoskeletal Research Center
Department of Orthopaedic Surgery
University of Pittsburgh Medical Center, PA

Introduction
Visualization tools that simulate experimentally obtained joint kinematics can provide much insight to their respective experiments. Experiments performed in the MSRC that examine the response of a joint to external loading conditions are one application where a visualization tool is useful. In the past, two virtual robots have been created using software that requires either complicated inputs or excessive and undocumented processing steps.

The objective of this project was to develop a general visualization tool to display the motion of our specimens during the robotic/UFS testing system experiments.

The Specific Aims were:
1) Create a virtual representation of our robotic/UFS testing system in SIMM 2.0.

2) Develop an easy and accessible method for incorporating experimental data (specimen geometry, joint kinematics) into the virtual model.

Methods
The Robotic/Universal Force-Moment Sensor (UFS) Testing System consists of a six-degree of freedom (DOF) manipulator, a UFS, and computer that records joint kinematics and forces. With a cadaveric knee specimen attached rigidly to the manipulator, a motion or external load can be applied to a joint, repeated, and in situ forces determined.

Software for Interactive Musculoskeletal Modeling (SIMM version 2.0, MusculoGraphics Inc., Evanston, IL) allows one to design graphics-based models of the musculoskeletal system. SIMM reads in surface models of bones or objects derived from CT scans and other sources. It can then create a serial linkage system with the surface models and animate them using kinematic data.

The advantages to using SIMM are its ability to interactively animate objects in real time using kinematic data. The disadvantages are that SIMM requires additional data processing for file conversion, compared to other software allowing multiple file type inputs.

To utilize the virtual model, users will input:
  • Surface Models of Bones
  • Joint Angles of Robot
  • Transformation Relationship: Bony Geometry to Robot
The resulting outputs are:
  • Virtual Experiment
  • Joint Motion
  • Ligament Length Changes
Creating the Virtual Robot
First, a kinematic linkage of a series of joints was developed. Various SIMM files were then written from the SIMM manual to create a simple robot. Rotations and joint distances of each link of the Unimate Puma robot-Model 762 were then established. A virtual representation of the robot from the Spine Research Group was initially inputted and modified. Extra elements such as the floor, walls, warning beacon, femur pedestal, and tibia clamp were added using CAD drawings and physical measurements. Geometry was designed in Truespace (Caligari Corporation, Mountain View, CA). Bony geometry and experimental kinematic data was obtained from the ACL Research Group and then added to the virtual robot. Finally, documentation of the data entry process for adding bony geometry and kinematic data was recorded.

Surface models derived from CT scans contained extensive numbers of polygons that hindered the real time visualization process. Visual Tool Kit (Kitware Inc., Clifton Park, NY) was used to reduce the number of polygons in each surface model (decimating), on an average from approximately 14000 to 5000 polygons.

Results and Discussion
The experimental kinematics were replayed and the robot successfully represented the quantitive data. Therefore, a successful visualization tool was developed.

I analyzed the radiographs to determine the femoral-tibial contact point. From that point I would measure the percentage of the liner from that point to the edge at the anterior side. This percentage will increase with increasing femoral rollback throughout flexion.



In the future we will continue writing the manual for the visualization process. An exact transformation for positioning the bony geometry will also be developed.

           

Acknowledgments
I would like to thank Dr. Savio L-Y. Woo, Dr. Richard Debski, and Dr. Lars Gilbertson for the opportunity of working here this summer. I would like to thank Eric Wong, Jorge Gil, Todd Doehring, Ted Rudy, and Dr. Debski for answering every question I had. And I would especially like to thank the summer students, Colleen OÕHara, and everybody else at the MSRC for making it fun and definitely interesting to work here.