A step towards dynamic foot classification: Functional grouping using ankle joint frontal plane motion in running.

Area of Science:

• Biomechanics
• Sports Science
• Human Movement Analysis

Background:

• Static foot classification assumes structure dictates function, but its validity is debated due to weak associations with dynamic motion.
• Calls exist for dynamic assessments to classify feet based on functional movement, yet methods are underexplored.

Purpose of the Study:

• To investigate homogenous subgroups of ankle joint complex (AJC) frontal plane motion within a group of runners.
• To develop and validate a method for dynamic foot type classification based on running kinematics.

Main Methods:

• K-means clustering analysis of barefoot running AJC frontal plane motion in 42 healthy adults.
• Statistical parametric mapping to compare kinematic differences between identified clusters.
• Agreement analysis between novel dynamic foot types and the Foot Posture Index (FPI-6).

Main Results:

• Two distinct clusters emerged: Neutral Dynamic Foot Type (Neutral_DFT) with less eversion, and Pronated Dynamic Foot Type (Pronated Dynamic_DFT) with more eversion.
• Significant differences (p < 0.001) in AJC eversion were found between clusters, with large effect sizes (g > 1).
• Low agreement (κ = 0.08) was observed between dynamic foot types and the FPI-6 static measure.

Conclusions:

• A novel protocol for classifying dynamic foot types based on AJC motion during running was demonstrated.
• Poor agreement between dynamic and static measures highlights their non-analogous nature.
• Static foot classification may not accurately reflect functional foot response during running; dynamic assessments are recommended.