Sign in
PhysiologybioRxiv
Preprint

Understanding the biomechanical and physiological responses to Advanced Footwear Technology in well-trained male and female runners

Yumna AlbertusiD, David LeithiD, Oloff BerghiD, Zach B. BarronsiD, Nicholas TamiD

Abstract

Advanced footwear technology (AFT) has transformed competitive running, yet individual and sex-specific responses to different AFT models remain unclear, particularly near race pace. This study examined running economy (RE) and gait biomechanics in response to three top-tier AFT models (Shoe A: adidas Pro Evo 2; Shoe B: Nike Alphafly 3; Shoe C: On CloudBoom Strike 2) in 14 male and 12 female well-trained runners at sex-specific submaximal speeds (16 and 14 km{middle dot}h-{superscript 1}). RE, spatiotemporal, and joint kinematic/kinetic data were collected via indirect calorimetry, accelerometry, and three-dimensional motion capture with force platforms. RE was significantly lower in Shoe C than Shoe A (males: 2.1%; females: 1.4%) and Shoe B (males: 1.9%; females: 0.9%), with 73% of runners responding favourably to Shoe C, a more consistent response than previously reported. Despite being lightest, Shoe A produced the poorest RE, challenging conventional mass-economy assumptions. Biomechanically, Shoe C elicited greater impact magnitude, lower ankle quasi-stiffness, and greater ankle angular velocity during early stance. Female runners showed smaller RE improvements, potentially related to lower running velocity and body mass limiting midsole engagement. The most efficient AFT enabled these well-trained runners to be more spring-like through tolerating higher forces and faster angular velocities without greater demand on metabolic cost.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMatties '24Blattmann '26Kuzmeski '26Rodrigo‐Car '24Bertschy '24Rodrigo‐Car '25
82% semantic matchPhysiology
Justin R. Matties, Joshua D. Kerr, K. Michael Rowley·bioRxiv·Nov 20, 2024· 5 citations