New considerations for collecting biomechanical data using wearable sensors: Number of level runs to define a stable running pattern with a single IMU

Abstract

Wearable technology can be used to quantify running biomechanical patterns in a runner’s natural environment, however, changes in external factors during outdoor running may influence a runner’s typical gait pattern. Therefore, the purpose of this study was to determine how many runs are needed to define a stable or typical running pattern. Six biomechanical variables were recorded using a single wearable sensor placed on the lower back during ten outdoor runs for twelve runners. Univariate and multivariate distributions were created and based on the probability density function, the percent of similar data points (within 95%) from each unique run for the same runner were determined. Stability was defined when the addition of data from a new run resulted in less than a 5% change in the probability density function. To cross-validate, the percent of similar data points at stability was compared between the same and different runners using a repeated-measures MANOVA (Bonferroni-corrected α = 0.007). The maximum number of runs needed to reach stability for univariate and multivariate analyses was four and five, respectively. There was a significant overall effect on similar data points between the same and different runners (p = 0.001), with a greater percent of similar data points for the same runner compared to other runners (p < 0.007). Based on biomechanical data collected using a single wearable sensor placed on the lower back, this is the first study to show that four (univariate) to five (multivariate) runs are needed to establish a stable running pattern in real-world settings.