Multibody kinematics optimization for motion reconstruction of the human upper extremity using potential field method

Area of Science:

• Biomechanics
• Kinetics and Kinematics

Background:

• Motion reconstruction is crucial for musculoskeletal simulations of human movement.
• Existing kinematic optimization methods lack computational efficiency and implementation simplicity.
• A need exists for a consistent and rapid method for reconstructing joint angles from motion capture data.

Purpose of the Study:

• To introduce a novel potential field method for forward dynamic motion reconstruction.
• To develop a computationally efficient and simple-to-implement technique for analyzing human movement.
• To validate the accuracy and speed of the proposed method against established techniques.

Main Methods:

• A potential field method utilizing virtual spring-dampers connecting skin markers to segment-fixed points.
• Solving equations of motion to reconstruct movement in a forward dynamic manner.
• Minimizing elastic potential and marker distance through virtual spring-damper forces.

Main Results:

• The potential field method achieves high computational speed (2.5ms per frame).
• Reconstruction accuracy is comparable to the least squares method (RMSE < 0.37mm, 1.87°).
• Soft tissue artifacts are well-compensated (RMSE < 1.66mm, 3.69°), with good reconstruction of shoulder and scapulothoracic joint rotations.

Conclusions:

• The proposed potential field method provides a computationally efficient and accurate solution for motion reconstruction.
• This method demonstrates robustness in handling soft tissue artifacts and reconstructing complex joint kinematics.
• The technique is suitable for large-scale biomechanical analyses requiring reliable and rapid human movement analysis.