Radial coordination variability: The radial vector coding for quantifying movement stability.

Area of Science:

• Biomechanics and Movement Science
• Human Movement Analysis
• Quantitative Physiology

Background:

• Traditional modified vector coding (mVC) uses planar angles to assess joint coordination.
• Current methods struggle to identify specific joint couplings impacting task performance.
• A need exists for a 3D analysis of movement coordination and variability.

Purpose of the Study:

• Introduce radial vector coding (rVC), a 3D extension of mVC.
• Develop a novel metric, radial coordination variability (CVr), to quantify 3D movement coordination.
• Analyze gait coordination and age-related differences using rVC.

Main Methods:

• Transformed joint trajectories from Cartesian to spherical coordinates.
• Calculated CVr from radial component fluctuations over time for pelvis, hip, knee, ankle, and foot.
• Applied rVC to gait data from 42 healthy adults across a range of walking speeds.

Main Results:

• CVr increased with speed and was higher in distal joints for young adults, indicating adaptive flexibility.
• Older adults exhibited reduced CVr at the ankle and knee, suggesting more constrained control.
• Significant interactions confirmed rVC captures functional coordination and age-related adaptations.

Conclusions:

• rVC provides an efficient, spatially integrated analysis of 3D movement coordination and variability.
• rVC avoids the complexity of multi-joint systems inherent in traditional mVC.
• This scalable method is applicable across diverse tasks and populations for coordination analysis.