A simple controller for the prediction of three-dimensional gait.

Area of Science:

• Biomechanics
• Orthopedic Surgery
• Computational Modeling

Background:

• Predicting functional outcomes after complex orthopedic procedures remains challenging.
• Existing musculoskeletal models require enhancement for simulating surgical alterations.

Purpose of the Study:

• To investigate forward dynamic modeling for predicting functional gait outcomes after lower extremity orthopedic surgery.
• To develop a 3D forward dynamics gait model incorporating muscle relocation/removal and osteotomies.
• To assess the model's ability to predict compensatory strategies in simulated pathological gait.

Main Methods:

• Developed a torque-actuated, 3D forward dynamics gait model, extending prior work.
• Incorporated subject-specific mechanical properties and an 'offset plus proportional' controller for lateral stability.
• Utilized kinematic constraints based on gait descriptors within an optimization algorithm.
• Integrated with the AnyBody Modeling System for musculoskeletal analysis and muscle activity insights.

Main Results:

• The model generates symmetric, cyclic gait efficiently (1 min/cycle on a 1GHz processor).
• The control scheme demonstrates robustness against mediolateral perturbations.
• Simulating weakened hip abductors allowed the model to predict compensatory gait trends.

Conclusions:

• Forward dynamic modeling shows potential for predicting functional outcomes in complex orthopedic lower extremity surgeries.
• The developed model provides insights into muscle activity and compensatory strategies.
• This approach can aid in surgical planning and the understanding of gait biomechanics post-intervention.