ECSS Paris 2023: OP-AP27
INTRODUCTION: Advanced footwear technology (AFT) improves running economy and performance compared with previous generations of running footwear, but little is known about the effects of minute differences in running economy between different AFT models during prolonged exercise. This study compared two AFT models with similar mechanical properties but with known differences in O2 cost of running during a prolonged run and its subsequent effect on performance. METHODS: An initial study using intra-day comparisons (three 6-min runs in each shoe, at 16 km/h) determined that the Nike Vaporfly 3 shoes (VF) showed 1.3% better running economy compared with the On Cloudboom eco 3 shoes (EB). These differences occurred even though both models showed reasonably similar levels of energy return at the forefoot (VF 6.4 J, EB 6.0 J). For the main study, twenty-one trained runners completed two 10-km trials at marathon pace followed immediately by a 2km time-trial (TT), one wearing Nike Vaporfly 3 shoes (VF) and one in On Cloudboom Echo 3 (EB) shoes, with each trial separated by one week. During the constant runs, gas exchange, heart rate (HR) and perceived exertion and were assessed. RESULTS: During the 10-km run, O2 cost for the VF was 1.6 ± 2.8 % lower compared with the EB (p = 0.012). No differences were detected in rate of perceived exertion between shoes (VF 5.0 ± 0.8 points, EB 5.2 ± 0.9 points, p = 0.270). No differences between shoes were detected for rate of change over time for O2 cost (p = 0.627), HR (p = 0.657), or perceived exertion (0.779). Runners performed the 2-km TT 1.8 ± 3.6 % faster wearing the VF (p = 0.031). CONCLUSION: Subtle differences in O2 cost between different AFT shoes are sufficient to elicit performance improvements. Gains in performance were higher than those previously estimated from gains in running economy alone, suggesting that other indirect benefits might be present beyond the direct metabolic savings. Factors other than energy return might be equally or more important in determining the running economy benefits of different AFT models.
Read CV Fernando BeltramiECSS Paris 2023: OP-AP27
INTRODUCTION: Player load monitoring via inertial measurement unit (IMU) in sports has been widely studied to prevent injuries, enhance training efficiency, and optimize performance [1]. The first and second ventilatory thresholds (VT1 and VT2) are valuable indicators of exercise intensity for identifying the transition between aerobic and anaerobic energy systems [2]. It has been found that varying running speeds influence player load [3]. However, the differences in player load between running speeds at ventilatory thresholds remain unclear. Therefore, the aim of this study was to monitor the changes in player load between ventilatory threshold running speeds in recreational runners. METHODS: Twenty-nine recreational runners (10km finish time: 48.10±5.87 min) performed maximal incremental running test with 3-minute stages on a treadmill (HP). An IMU (100Hz, Vicon) was placed on the runners’ lower back (L3–L5) to collect triaxial acceleration data during the incremental test. The raw acceleration data were filtered at 20Hz using a low-pass Blackman filter (AcqKnowledge). The 1-minute root mean square (RMS) of the triaxial player load (PLT) were calculated. The 1-minute RMS of the single-axis player load in the anteroposterior (PLAP), mediolateral (PLML), and vertical (PLV) axes were also calculated. The percentage contribution of each axis was calculated by dividing the RMS of uniaxial player load by the RMS of triaxial player load. Participants’ gas exchange data were continuously measured using a portable gas analyzer (Cortex). The 1-minute averaged gas exchange data were used to determine the VT1 and VT2 running speeds. The last-minute IMU and Cortex data from each stage of the incremental test were used for analysis. A paired-samples t-test was used to evaluate differences in player load between VT1 and VT2 speeds. The significant level was set at p<.05. The effect size was calculated using Cohens d. RESULTS: The RMSPLV (VT1 speed: 4.25±0.86, VT2 speed: 4.87±0.88; p<.001, d=-1.87), RMSPLML (VT1 speed: 1.87±0.60, VT2 speed: 2.34±0.80; p<.001, d=-1.37), RMSPLAP (VT1 speed: 1.81±0.52, VT2 speed: 2.41±0.64; p<.001, d=-1.78), RMSPLT (VT1 speed: 5.04±0.92, VT2 speed: 6.00±0.93; p<.001, d=-2.38), RatioPLV (VT1 speed: 84.30±6.14, VT2 speed: 81.26±7.24; p<.001, d=0.94), and RatioPLAP (VT1 speed: 36.47±9.06, VT2 speed: 40.82±10.42; p<.001, d=-1.04) changed significantly between VT1 and VT2 speeds. However, the RatioPLML (VT1 speed: 37.06±8.78, VT2 speed: 38.56±9.57; p=.11, d=-0.31) did not change significantly between VT1 and VT2 speeds. CONCLUSION: The RMSPLV, RMSPLML, RMSPLAP, RMSPLT, RatioPLAP increased significantly at VT2 speed. Interestingly, the RatioPLV decreased significantly at VT2 speed. Additionally, the RatioPLML did not change significantly at VT2 running speed. The results of this study suggest that PL in anteroposterior direction may play a more influential role at VT2 speed in recreational runners.
Read CV Chuan Fang HouECSS Paris 2023: OP-AP27
INTRODUCTION: Advanced Footwear Technology (AFT) encompasses multiple innovations including the increase in longitudinal bending stiffness achieved through the integration of a plate and a softer and more resilient foam within the midsole. They have been shown to improve running performance and running economy (1). While performance benefits have commonly been investigated in road running, AFT is beginning to influence footwear used in trail running. Therefore, research is needed to investigate the effect of AFT in trail running footwear. In this study, we aimed to compare the effect of traditional (TRADI) and advanced foam technologies (PROTO) on running economy and perceptual measures across flat, up and down-hill gradients. METHODS: Fourteen well-trained athletes (78.9 ± 25.3 km/week) completed assessments on the treadmill with FLAT (0% gradient, 14 km.h−1), UP (+10%, 8 km.h−1) and DOWN (-10%, 14 km.h−1) conditions. Two shoes (TRADI v PROTO) were randomly allocated in a counterbalanced order, with a replicate in each condition. The shoes differed in their midsole foam type but were otherwise matched. PROTO included a softer and more resilient foam than TRADI (deformation: 23.63 v 19.46 mm; energy return: 9.97 v 6.86 J). Oxygen consumption, HR, RPE and affect (pleasure and arousal) were collected and averaged for each replicate. General Linear Mixed Model were used for the statistical analysis with a significance set at 0.05. RESULTS: Across conditions, oxygen consumption was lower in PROTO than TRADI (44.9 ± 0.6 v 45.4 ± 0.6 ml.-1.kg-1.min-1 respectively) with a small effect size (p=0.008; d=0.47). This equates to a superior running economy in the PROTO across all the conditions of 1.1%. The interaction between condition and shoes was not significant (p=0.050) although the tendency that an improvement may be more pronounced in the FLAT (+2.1%) and UP (+1.0%) conditions, compared to DOWN (+0%) may inform future, larger investigations. HR was lower in PROTO compared to TRADI (p< 0.001; 145 ± 3.5 v 146 ± 3.5 bpm respectively) with a large effect size likely explained by the consistency of the change across all participants (d=1.19). RPE was lower (p=0.010) and pleasure higher (p=0.025) in PROTO compared to TRADI with a medium effect size. No effect on arousal was identified (p=0.730). CONCLUSION: The findings of this study suggest that a softer and more resilient foam in trail running shoes can improve running economy, reduce HR and perceived exertion and increase pleasure while running at different gradient in a well-trained athlete population. REFERENCES: 1.Hoogkamer et al., 2017
Read CV Melissa MuzeauECSS Paris 2023: OP-AP27