A Simple Algorithm for Assimilating Marker-Based Motion Capture Data During Periodic Human Movement Into Models of...

Area of Science:

• Biomechanics
• Human Movement Analysis
• Computational Modeling

Background:

• Reflective-marker-based motion capture is crucial for quantitative human movement analysis using multi-rigid-body models.
• Soft tissue artifact (STA) introduces inaccuracies by causing marker motion relative to the skeletal system.

Purpose of the Study:

• To develop a simple algorithm to eliminate STA from motion capture data during periodic human movements.
• To ensure assimilated motion in multi-rigid-body models is unaffected by STA.

Main Methods:

• The algorithm assumes STA time-profiles are periodic during movements like walking.
• Unknown STA profiles are represented using Fourier series.
• Fourier coefficients are optimized based on STA periodicity and kinematic constraints of rigid links.

Main Results:

• The algorithm accurately estimates STA and retrieves the true, non-STA-affected motion in a numerical gait model.
• The STA removal processing significantly enhances the accuracy of inverse dynamics analysis.

Conclusions:

• The proposed algorithm effectively removes soft tissue artifact from periodic human movement data.
• This method offers improved accuracy for quantitative gait and biomechanical analyses.