Mechanical model of orthopaedic drilling for augmented-haptics-based training

Area of Science:

• Orthopaedic biomechanics
• Haptic simulation technology
• Surgical robotics

Background:

• Simulating anatomic variability in bone is crucial for realistic surgical training.
• Existing haptic devices lack the force capabilities for accurate simulation of clinical bone drilling.
• Augmented-haptic feedback offers a potential solution by integrating physical and virtual elements.

Purpose of the Study:

• To develop a predictive model for axial force during simulated orthopaedic bone drilling.
• To enable augmented-haptic feedback systems to simulate anatomic variability in bone.
• To achieve force generation consistent with clinical bone drilling procedures.

Main Methods:

• Collected kinematic data from drilling synthetic bone samples with an instrumented linkage.
• Measured axial force using a force sensor integrated into the bone fixture.
• Developed a nonlinear predictive model relating force to axial position and velocity.

Main Results:

• The predictive model achieved a normalized root-mean-square error (RMSE) of 0.11 N.
• The model accurately predicted forces across bones with varying geometry and density.
• The model successfully captured variations in cortical and cancellous bone properties.

Conclusions:

• A predictive model can effectively simulate anatomic variability in bone for haptic feedback.
• This approach enhances the realism of virtual surgical training environments.
• The developed model facilitates force generation exceeding current commercial haptic device capabilities.