A model of the soft tissue artefact rigid component

Area of Science:

• Biomechanics
• Motion Analysis
• Medical Imaging

Background:

• Stereophotogrammetry with skin markers is crucial for skeletal movement reconstruction.
• Soft-tissue artefact (STA) significantly impacts the accuracy of marker-based motion capture.
• Understanding STA as a deformable shape with rigid and non-rigid components is key.

Purpose of the Study:

• To propose a mathematical model for estimating the rigid component of STA.
• To validate the model's ability to compensate for STA in skeletal movement analysis.
• To quantify the improvement in joint kinematics accuracy after STA compensation.

Main Methods:

• Developed a mathematical model to estimate the rigid component of STA based on joint rotations.
• Calibrated the model using simultaneous pin- and skin-marker data from running volunteers.
• Estimated knee joint kinematics using raw and STA-compensated skin-marker data.

Main Results:

• The model successfully calibrated for thigh and shank, with a low root mean square difference for the rigid STA component (1.1(0.8)mm).
• STA compensation significantly reduced inaccuracies in knee joint kinematics: flexion/extension (6% to 1%), other rotations (43% to 18%), and linear displacements (69% to 25%).

Conclusions:

• The proposed mathematical model effectively estimates STA, enabling accurate compensation in skeletal movement analysis.
• This model enhances the reliability of bone pose and joint kinematics estimation.
• The findings support the use of this model for artefact compensation and comparative assessments in motion analysis.