Dynamic simulation of knee-joint loading during gait using force-feedback control and surrogate contact modelling

Area of Science:

• Biomechanics
• Human Gait Analysis
• Musculoskeletal Modeling

Background:

• Accurate estimation of tibiofemoral contact forces is crucial for understanding knee joint loading during human locomotion.
• Existing computational models vary in complexity and accuracy, particularly for dynamic activities like stair descent.

Purpose of the Study:

• To evaluate the accuracy of a novel forward-dynamics simulation incorporating force-feedback control (FFC) for predicting knee joint loading during gait.
• To compare FFC with other common simulation methods, including computed muscle control (CMC) and static optimization (SO), using multi-DOF and simplified knee models.

Main Methods:

• Multi-body, muscle-driven, forward-dynamics simulations were performed using a 6-DOF knee model with FFC.
• Simulations tracked motion capture data from level walking and stair descent in individuals with instrumented knee implants.
• Tibiofemoral contact force errors were quantified and compared across FFC, CMC6 (6-DOF), CMC1 (1-DOF), and SO (1-DOF) models.

Main Results:

• FFC and CMC6 (6-DOF) showed comparable tibiofemoral contact force predictions during level walking.
• FFC demonstrated superior accuracy over CMC6, CMC1, and SO for stair descent simulations.
• CMC1 (1-DOF) consistently yielded the least accurate predictions for both walking and stair descent.

Conclusions:

• Force-feedback control (FFC) combined with a multi-DOF knee model offers reliable knee-joint loading estimates during gait simulations.
• The findings highlight the importance of advanced modeling techniques, particularly for dynamic activities like stair descent, to improve biomechanical insights.