Intra-Articular Knee Contact Force Estimation During Walking Using Force-Reaction Elements and Subject-Specific Joint...

Area of Science:

• Biomechanics
• Orthopedic Surgery
• Medical Device Engineering

Background:

• Instrumented knee implants reveal individual joint loading variations.
• Musculoskeletal models simulate body kinetics and joint forces.
• Understanding knee contact forces is crucial for joint health and arthroplasty.

Purpose of the Study:

• Develop a knee contact model using inverse dynamics optimization to predict knee contact forces.
• Investigate the impact of joint constraints on the accuracy of knee contact force predictions.
• Enhance the prediction of in vivo knee contact forces for improved total knee replacement (TKR) design.

Main Methods:

• Developed a knee contact model with 32 reaction force elements on a tibial insert within a full-body musculoskeletal model.
• Utilized motion and external force data from walking trials provided by the Sixth Grand Challenge Competition.
• Compared model predictions with in vivo knee contact force measurements from an instrumented knee implant.

Main Results:

• A basic model predicted knee contact forces with RMSEs of 165 N (medial) and 288 N (lateral).
• Adjusting joint constraints and marker locations for valgus alignment improved predictions (RMSEs of 144 N medial, 179 N lateral).
• Coefficients of determination (R2) showed improved prediction accuracy with subject-specific adjustments.

Conclusions:

• The developed knee contact model, especially with subject-specific joint parameters, can reasonably predict in vivo knee contact forces.
• This predictive model holds potential for advancing the development and refinement of knee arthroplasty.
• Accurate prediction of knee contact forces can inform surgical techniques and implant design for better patient outcomes.