Change the direction: 3D optimal control simulation by directly tracking marker and ground reaction force data.

Area of Science:

• Biomechanics
• Computational modeling
• Sports science

Background:

• Optimal control simulations offer dynamically consistent musculoskeletal motion reconstruction.
• Traditional methods often track generalized coordinates, propagating errors from inverse kinematics.
• Directly tracking marker data in simulations presents an alternative approach.

Purpose of the Study:

• To develop and evaluate an optimal control simulation method for reconstructing 3D full-body motions by directly tracking marker and ground reaction force data.
• To compare this marker tracking approach with traditional coordinate tracking and inverse kinematics methods for motion reconstruction.

Main Methods:

• Developed an optimal control simulation framework for 3D full-body musculoskeletal models.
• Directly tracked optical motion capture marker data and ground reaction forces.
• Evaluated the method using running and v-cut trials from 10 participants, comparing marker tracking, coordinate tracking, and inverse kinematics.

Main Results:

• Marker tracking simulations showed slightly higher marker position deviations than inverse kinematics but significantly improved accuracy over coordinate tracking.
• Coordinate tracking resulted in nearly double the marker position deviations compared to marker tracking.
• Wall time for simulations increased 3-4 times with marker tracking versus coordinate tracking.

Conclusions:

• Optimal control simulations can effectively reconstruct change-of-direction running motions by directly tracking marker and ground reaction force data.
• Direct marker tracking in optimal control simulations offers improved marker accuracy compared to coordinate tracking.
• This method is recommended when precise marker tracking is essential for movement reconstruction.