The effect of uphill stride manipulation on race walking gait

Gait Variability at Different Walking Speeds

Gait variability (GV) is a crucial measure of inconsistency of muscular activities or body segmental movements during repeated tasks. Hence, GV might serve as a relevant and sensitive measure to quantify adjustments of walking control. However, it has not been clarified whether GV is associated with walking speed, a clarification needed to exploit effective better bilateral coordination level. For this aim, fourteen male students (age 22.4 ± 2.7 years, body mass 74.9 ± 6.8 kg, and body height 1.78 ± 0.05 m) took part in this study. After three days of walking 1 km each day at a self-selected speed (SS) on asphalt with an Apple Watch S. 7 (AppleTM, Cupertino, CA, USA), the participants were randomly evaluated on a treadmill at three different walking speed intensities for 10 min at each one, SS - 20%/SS + 20%/ SS, with 5 min of passive recovery in-between. Heart rate (HR) was monitored and normalized as %HRmax, while the rate of perceived exertion (RPE) (CR-10 scale) was asked after each trial. Kinematic analysis was performed, assessing the Contact Time (CT), Swing Time (ST), Stride Length (SL), Stride Cycle (SC), and Gait Variability as Phase Coordination Index (PCI). RPE and HR increased as the walking speed increased (p = 0.005 and p = 0.035, respectively). CT and SC decreased as the speed increased (p = 0.0001 and p = 0.013, respectively), while ST remained unchanged (p = 0.277). SL increased with higher walking speed (p = 0.0001). Conversely, PCI was 3.81 ± 0.88% (high variability) at 3.96 ± 0.47 km·h-1, 2.64 ± 0.75% (low variability) at SS (4.94 ± 0.58 km·h-1), and 3.36 ± 1.09% (high variability) at 5.94 ± 0.70 km·h-1 (p = 0.001). These results indicate that while the metabolic demand and kinematics variables change linearly with increasing speed, the most effective GV was observed at SS. Therefore, SS could be a new methodological approach to choose the individual walking speed, normalize the speed intensity, and avoid a gait pattern alteration.

Marathon shoes vs. track spikes: a crossover pilot study on metabolic demand at different speeds in experienced runners

The aim of this study was to assess the metabolic cost (Cr) with marathon shoes (Adidas Adizero 3 [AA]) vs. track spikes (Nike Zoom Matumbo 3 [NZM]) on track. For this, five experienced runners were randomly assessed (NZM/AA) on a running track at 73% and 85% of best performance speed on 1500-m race. At first, speed (4.39 ± 0.53 m·s^-1), Crs with AA and NZM resulted 3.63 ± 0.29 and 3.64 ± 0.43 J·kg^-1·m^-1 (+0.3% with NZM, effect size [ES] small and p = 0.951), respectively. Besides, at second speed (5.20 ± 0.18 m·s^-1), Crs were 4.09 ± 0.28 and 4.07 ± 0.22 J·kg^-1·m^-1 (-0.5% with NZM, ES small and p = 0.919) with AA and NZM, respectively. It resulted in an increased Cr (+12.2%) between s1 and s2 with both shoe conditions (ES large and p = 0.009 and 0.011 with AA and NZM, respectively). There is a pattern yet to be confirmed for track spikes to become more beneficial at higher speeds (when duty factor becomes lower and therefore grip on track is crucial).

IART: Inertial Assistant Referee and Trainer for Race Walking

This paper presents IART, a novel inertial wearable system for automatic detection of infringements and analysis of sports performance in race walking. IART algorithms are developed from raw inertial measurements collected by a single sensor located at the bottom of the vertebral column (L5-S1). Two novel parameters are developed to estimate infringements: loss of ground contact time and loss of ground contact step classification; three classic parameters are indeed used to estimate performance: step length ratio, step cadence, and smoothness. From these parameters, five biomechanical indices customized for elite athletes are derived. The experimental protocol consists of four repetitions of a straight path of 300 m on a long-paved road, performed by nine elite athletes. Over a total of 1620 steps (54 sequences of 30 steps each), the average accuracy of correct detection of loss of ground contact events is equal to 99%, whereas the correct classification of the infringement is equal to 87% for each step sequence, with a 92% of acceptable classifications. A great emphasis is dedicated on the user-centered development of IART: an intuitive radar chart representation is indeed developed to provide practical usability and interpretation of IART indices from the athletes, coaches, and referees perspectives. The results of IART, in terms of accuracy of its indices and usability from end-users, are encouraging for its usage as tool to support athletes and coaches in training and referees in real competitions.