A functional foot type classification with cluster analysis based on plantar pressure distribution during jogging.

Area of Science:

• Biomechanics
• Sports Science
• Human Movement Analysis

Background:

• Plantar pressure analysis is crucial for understanding foot function during locomotion.
• Existing data primarily focuses on walking, with limited reference datasets for jogging.
• Variations in foot loading patterns can impact performance and injury risk.

Purpose of the Study:

• To create a reference dataset for peak pressures and pressure-time integrals during jogging.
• To compare jogging plantar pressure data with existing walking data.
• To develop a foot type classification based on plantar pressure data.

Main Methods:

• Plantar pressure data were collected from 215 healthy young adults running at 3.3 m/s.
• Peak pressures, regional impulses, and relative regional impulses were measured using pressure and force platforms.
• K-means cluster analysis was employed to identify distinct pressure loading patterns.

Main Results:

• Reliable measurements (ICC > 0.75) were obtained for peak pressures and impulses, with negligible gender and asymmetry effects (except heel).
• Jogging exhibited higher peak pressures and impulses compared to walking, with distinct hallux loading.
• Four forefoot pressure loading patterns were identified: medial M1, medial M2, central, and central-lateral.

Conclusions:

• The established reference dataset provides valuable insights into jogging biomechanics.
• Identified foot loading patterns offer a basis for functional interpretation of foot behavior during slow running.
• Findings highlight differences between walking and jogging foot loading, relevant for athletic performance and injury prevention.