Development of a Bone Drilling Simulation System With Force Feedback

Abstract

We present the development of a bone drilling simulation system to simulate on a PC the drilling operations commonly used in orthopedic surgery. A drilling force model is obtained by performing regression of measured drilling force versus process and material parameters. A haptic rendering algorithm consisting collision detection and force generation is also developed. The overall simulation of the developed system runs two threads in parallel: (1) haptics thread, which obtains the position and orientation of the virtual drill and provides force feedback and (2) graphics thread, which is dedicated to real-time rendering of volumetric data.

Force and Torque Modeling for the Drilling of Bone for use in Orthopaedic Haptic Simulation Systems

“…This work focuses on the contributions to haptic rendering and, thus, graphic rendering and collision detection will not be further discussed. For additional information regarding graphic rendering and collision detection refer to [14][15][16][17][18][19][20]. The haptic rendering process for orthopaedic surgical simulation systems has received much less attention from research groups than that of graphic rendering process.…”

“…Subsequent studies explored the possibility of developing unique empirical models for predicting cutting force and torque during the drilling of bone. It was shown that the drilling thrust force could be modeled using regression techniques and written as a function of drill speed, feed rate, and material density [15]. The empirical force model was presented in the following form [15]:…”

“…Here, f is the feed rate in mm/sec, ρ is the material density in g/cc, and C T , C N , C f , and C D are the constants of the model. Next, the logarithm of the equation was taken yielding the following [15]:…”

“…Using the collected experimental data, a QR decomposition algorithm was implemented yielding the model constants. These constants were reported as [15]:…”

“…In another work, an empirical formulation based exclusively on spindle speed, feed rate, and material density was utilized to generate haptic feedback [15]. Later, another haptic platform was created that employed a spring-damper model to provide predicted force/torque feedback [15].…”