Differences between Sexes and Speed Levels in Pelvic 3D Kinematic Patterns during Running Using an Inertial Measurement Unit (IMU).

This study aimed to assess the 3D kinematic pattern of the pelvis during running and establish differences between sexes using the IMU sensor for spatiotemporal outcomes, vertical acceleration symmetry index, and ranges of motion of the pelvis in the sagittal, coronal, and transverse planes of movement. The kinematic range in males was 5.92°-6.50°, according to tilt. The range of obliquity was between 7.84° and 9.27° and between 9.69° and 13.60°, according to pelvic rotation. In females, the results were 6.26°-7.36°, 7.81°-9.64°, and 13.2°-16.13°, respectively. Stride length increased proportionally to speed in males and females. The reliability of the inertial sensor according to tilt and gait symmetry showed good results, and the reliability levels were excellent for cadence parameters, stride length, stride time, obliquity, and pelvic rotation. The amplitude of pelvic tilt did not change at different speed levels between sexes. The range of pelvic obliquity increased in females at a medium speed level, and the pelvic rotation range increased during running, according to speed and sex. The inertial sensor has been proven to be a reliable tool for kinematic analysis during running.

The Relationship between VO2max, Power Management, and Increased Running Speed: Towards Gait Pattern Recognition through Clustering Analysis.

Triathlon has become increasingly popular in recent years. In this discipline, maximum oxygen consumption (VO2max) is considered the gold standard for determining competition cardiovascular capacity. However, the emergence of wearable sensors (as Stryd) has drastically changed training and races, allowing for the more precise evaluation of athletes and study of many more potential determining variables. Thus, in order to discover factors associated with improved running efficiency, we studied which variables are correlated with increased speed. We then developed a methodology to identify associated running patterns that could allow each individual athlete to improve their performance. To achieve this, we developed a correlation matrix, implemented regression models, and created a heat map using hierarchical cluster analysis. This highlighted relationships between running patterns in groups of young triathlon athletes and several different variables. Among the most important conclusions, we found that high VO2max did not seem to be significantly correlated with faster speed. However, faster individuals did have higher power per kg, horizontal power, stride length, and running effectiveness, and lower ground contact time and form power ratio. VO2max appeared to strongly correlate with power per kg and this seemed to indicate that to run faster, athletes must also correctly manage their power.