Effects of footwear midsole thickness on running biomechanics.

Shoe manufacturers launch running shoes with increased (e.g., maximalists) or decreased (e.g., minimalists) midsole thickness and claim that they may prevent running injury. Previous studies tested footwear models with different midsole thicknesses on the market but the shoe construct was not strictly comparable. Therefore, in the present study, we examined the effect of midsole thickness, from 1-mm to 29-mm, in a standard test shoe prototype on the vertical loading rates, footstrike angle and temporal spatial parameters in distance runners. Fifteen male habitual rearfoot strikers were recruited from local running clubs. They were asked to run on an instrumented treadmill in shoes with different midsole thicknesses. We found significant interactions between midsole thickness with vertical loading rates (p < 0.001), footstrike angle (p = 0.013), contact time (p < 0.001), cadence (p = 0.003), and stride length (p = 0.004). Specifically, shoes with thinner midsole (1- and 5-mm) significantly increased the vertical loading rates and shortened the contact time, when compared with thicker midsole shoes (25- and 29-mm). However, we did not observe any substantial differences in the footstrike angle, cadence and stride length between other shod conditions. The present study provides biomechanical data regarding the relationship between full spectrum midsole thicknesses and running biomechanics in a group of rearfoot strikers.

Measurement agreement between a newly developed sensing insole and traditional laboratory-based method for footstrike pattern detection in runners.

This study introduced a novel but simple method to continuously measure footstrike patterns in runners using inexpensive force sensors. Two force sensing resistors were firmly affixed at the heel and second toe of both insoles to collect the time signal of foot contact. A total of 109 healthy young adults (42 males and 67 females) were recruited in this study. They ran on an instrumented treadmill at 0°, +10°, and -10° inclinations and attempted rearfoot, midfoot, and forefoot landings using real time visual biofeedback. Intra-step strike index and onset time difference between two force sensors were measured and analyzed with univariate linear regression. We analyzed 25,655 footfalls and found that onset time difference between two sensors explained 80-84% of variation in the prediction model of strike index (R-squared = 0.799-0.836, p<0.001). However, the time windows to detect footstrike patterns on different surface inclinations were not consistent. These findings may allow laboratory-based gait retraining to be implemented in natural running environments to aid in both injury prevention and performance enhancement.