Effects of Optimization Technique on Simulated Muscle Activations and Forces

Area of Science:

• Biomechanics
• Computational modeling
• Human movement analysis

Background:

• OpenSim is widely used for simulating musculoskeletal dynamics.
• Static optimization (SO) and computed muscle control (CMC) are common techniques for estimating muscle forces.
• Previous studies suggest differences between SO and CMC, but their comparative accuracy and model dependency remain unclear.

Purpose of the Study:

• To quantitatively compare SO and CMC estimates of muscle activations and forces during gait.
• To evaluate the influence of model choice (Gait2392, Full Body Running) on these estimates.
• To validate simulations against experimental muscle activation and joint torque data.

Main Methods:

• Simulated gait using SO and CMC in OpenSim (v3.1) for 6 subjects per model.
• Validated simulated muscle activations and joint torques against experimental data.
• Analyzed differences in muscle forces, activations, and co-contraction indices between SO and CMC.

Main Results:

• Agreement between simulated and experimental muscle activations varied by optimization technique (soleus, tibialis anterior).
• Knee extension torque error was greater with CMC than SO.
• CMC generally produced higher muscle forces, activations, and co-contraction indices, with greater sensitivity to model choice.

Conclusions:

• The choice of optimization technique (SO vs. CMC) and musculoskeletal model significantly impacts simulated muscle function during gait.
• CMC's advanced features (passive forces, activation-contraction dynamics, PD controller) contribute to observed differences.
• Validation against simultaneous experimental activation data is crucial for selecting appropriate models and optimization techniques.