Speed-Dependent Multivariate Coordination Variability Using an Ellipse-Based Vector Coding Method.

Area of Science:

• Biomechanics
• Movement Science
• Kinesiology

Background:

• Vector coding is standard for movement analysis but often limited to two joints.
• Human movement involves complex interactions across multiple joints.
• Ellipse-based vector coding allows for higher-dimensional coordination analysis.

Purpose of the Study:

• To examine bivariate and trivariate coordination variability in the lower extremity across walking speeds.
• To compare coordination dynamics between slow and fast walking using ellipse-based vector coding.
• To identify the role of specific joints (hip, knee, ankle) in coordination variability.

Main Methods:

• Employed an ellipse-based vector coding method to analyze lower extremity coordination.
• Calculated mean between-cycle variability during stance and swing phases.
• Utilized statistical nonparametric mapping and cross-correlation analyses.

Main Results:

• Coordination variability (bivariate and trivariate) increased at faster walking speeds.
• High cross-correlation (0.82–0.96) was found between bivariate and trivariate couplings involving the ankle.
• The ankle joint demonstrated a significant role in driving coordination variability.

Conclusions:

• Faster walking alters lower extremity coordination dynamics, increasing variability.
• Ankle-involved bivariate couplings effectively represent trivariate coordination patterns during walking.
• The findings highlight the ankle's importance in modulating gait variability.