Running biomechanics and ethnicity can influence running economy (RE), which is a critical factor of running performance. Our aim was to compare RE of South East Asian (SEA) and non-South East Asian ...(non-SEA) runners at several endurance running speeds (10-14 km/h) matched for on-road racing performance and sex. Secondly, we explored anthropometric characteristics and relationships between RE and anthropometric and biomechanical variables. SEA were 6% less economical (p = 0.04) than non-SEA. SEA were lighter and shorter than non-SEA, and had lower body mass indexes and leg lengths (p ≤ 0.01). In terms of biomechanics, a higher prevalence of forefoot strikers in SEA than non-SEA was seen at each speed tested (p ≤ 0.04). Furthermore, SEA had a significantly higher step frequency (p = 0.02), shorter contact time (p = 0.04), smaller footstrike angle (p < 0.001), and less knee extension at toe-off (p = 0.03) than non-SEA. Amongst these variables, only mass was positively correlated to RE for both SEA (12 km/h) and non-SEA (all speeds); step frequency, negatively correlated to RE for both SEA (10 km/h) and non-SEA (12 km/h); and contact time, positively correlated to RE for SEA (12 km/h). Despite the observed anthropometric and biomechanical differences between cohorts, these data were limited in underpinning the observed RE differences at a group level. This exploratory study provides preliminary indications of potential differences between SEA and non-SEA runners warranting further consideration. Altogether, these findings suggest caution when generalizing from non-SEA running studies to SEA runners.
Contact time (tc) relies upon the accuracy of foot-strike and toe-off events, for which ground reaction force (GRF) is the gold standard. However, force plates are not always available, e.g., when ...running on a noninstrumented treadmill. In this situation, a kinematic algorithm (KA) – an algorithm based on motion capture data – might be used if it performs equally for all foot-strike angles across speeds. The purpose of this study was to propose a novel KA, using a combination of heel and toe kinematics (three markers per foot), to detect foot-strike and toe-off and compare it to GRF at different speeds and across foot-strike angles. One hundred runners ran at 9 km/h, 11 km/h, and 13 km/h. Force data and whole-body kinematic data were acquired by an instrumented treadmill and optoelectronic system. Foot-strike and toe-off showed small systematic biases between GRF and KA at all speeds (≤5 ms), except toe-off at 11 km/h (no bias). The root mean square error (RMSE) was ≤9 ms and was mostly constant across foot-strike angles for toe-off (7.4 ms) but not for foot-strike (4.1–11.1 ms). Small systematic biases (≤8 ms) and significant differences (P ≤ 0.01) were reported for tc at all speeds, and the RMSE was ≤14 ms (≤5%). The RMSE for tc increased with increasing foot-strike angle (3.5–5.4%). Nonetheless, this novel KA computed smaller errors than existing methods for foot-strike, toe-off, and tc. Therefore, this study supports the use of this novel KA to accurately estimate foot-strike, toe-off, and tc from kinematic data obtained during noninstrumented treadmill running independent of the foot-strike angle.
Peak vertical ground reaction force (Fz,max), contact time (tc), and flight time (tf) are key variables of running biomechanics. The gold standard method (GSM) to measure these variables is a force ...plate. However, a force plate is not always at hand and not very portable overground. In such situation, the vertical acceleration signal recorded by an inertial measurement unit (IMU) might be used to estimate Fz,max, tc, and tf. Hence, the first purpose of this study was to propose a method that used data recorded by a single sacral-mounted IMU (IMU method: IMUM) to estimate Fz,max. The second aim of this study was to estimate tc and tf using the same IMU data. The vertical acceleration threshold of an already existing IMUM was modified to detect foot-strike and toe-off events instead of effective foot-strike and toe-off events. Thus, tc and tf estimations were obtained instead of effective contact and flight time estimations. One hundred runners ran at 9, 11, and 13 km/h. IMU data (208 Hz) and force data (200 Hz) were acquired by a sacral-mounted IMU and an instrumented treadmill, respectively. The errors obtained when comparing Fz,max, tc, and tf estimated using the IMUM to Fz,max, tc, and tf measured using the GSM were comparable to the errors obtained using previously published methods. In fact, a root mean square error (RMSE) of 0.15 BW (6%) was obtained for Fz,max while a RMSE of 20 ms was reported for both tc and tf (8% and 18%, respectively). Moreover, even though small systematic biases of 0.07 BW for Fz,max and 13 ms for tc and tf were reported, the RMSEs were smaller than the smallest real differences Fz,max: 0.28 BW (11%), tc: 32.0 ms (13%), and tf: 32.0 ms (30%), indicating no clinically important difference between the GSM and IMUM. Therefore, these results support the use of the IMUM to estimate Fz,max, tc, and tf for level treadmill runs at low running speeds, especially because an IMU has the advantage to be low-cost and portable and therefore seems very practical for coaches and healthcare professionals.
Abstract
Runners were classified using their duty factor (DF) and using their foot-strike pattern (FSP; rearfoot, midfoot, or forefoot strikers), determined from their foot-strike angle (FSA). High ...and low DF runners showed different FSPs but DF was assumed to not only reflect what happens at initial contact with the ground (more global than FSP/FSA). Hence, FSP and DF groups should not necessarily be constituted by the same runners. However, the relation between FSP and DF groups has never been investigated, leading to the aim of this study. One hundred runners ran at 9, 11, and 13 km/h. Force data (1000 Hz) and whole-body kinematics (200 Hz) were acquired by an instrumented treadmill and optoelectronic system and were used to classify runners according to their FSA and DF. Weak correlations were obtained between FSA and DF values and a sensitivity of 50% was reported between FSP and DF groups, i.e., only one in two runners was attributed to the DF group supposedly corresponding to the FSP group. Therefore, ‘local’ FSP/FSA and DF do not represent similar running pattern information when investigated at the individual level and DF should be preferred to FSP/FSA when evaluating the global running pattern of a runner.
Equations predicting stride frequency (SF) and duty factor (DF) solely based on running speed have been proposed. However, for a given speed, kinematics vary depending on the global running pattern ...(GRP), i.e., the overall individual movement while running, which depends on the vertical oscillation of the head, antero-posterior motion of the elbows, vertical pelvis position at ground contact, antero-posterior foot position at ground contact, and strike pattern. Hence, we first verified the validity of the aforementioned equations while accounting for GRP. Kinematics during three 50-m runs on a track (
= 20) were used with curve fitting and linear mixed effects models. The percentage of explained variance was increased by ≥133% for DF when taking into account GRP. GRP was negatively related to DF (
= 0.004) but not to SF (
= 0.08), invalidating DF equation. Second, we assessed which parameters among anthropometric characteristics, sex, training volume, and GRP could relate to SF and DF in addition to speed, using kinematic data during five 30-s runs on a treadmill (
= 54). SF and DF linearly increased and quadratically decreased with speed (
< 0.001), respectively. However, on an individual level, SF was best described using a second-order polynomial equation. SF and DF showed a non-negligible percentage of variance explained by random effects (≥28%). Age and height were positively and negatively related to SF (
≤ 0.05), respectively, while GRP was negatively related to DF (
< 0.001), making them key parameters to estimate SF and DF, respectively, in addition to speed.
Introduction Primitive reflexes (PR) induce involuntary automatic movements in response to specific stimuli. This study aimed to determine the prevalence of active PR in young high-level football ...players. Methodology Sixty-nine national-level football players from a French academy were tested (17.0 ± 1.4 years; 69.6 ± 8.0 kg; 178.9 ± 6.9 cm) to evaluate the persistence of PR, following the methodology of the Institute for Neuro-Physiological Psychology (INPP) and the classification by a global score (GS). Based on the sum of seven tests, each was rated between 0 = null and 4 = max. The GS is classified into five categories from no activity to maximal (0–1 = no activity, 2–7 = low, 8–13 = medium, 14–21 = high, and 22–28 = maximal). Result Around two-thirds (68.1%) of players presented active PR at different activity levels. Among them, a small proportion (7.2%) had medium GS, while 60.9% had a low GS. The GS was not dependent on field position or the age of the players ( p > 0.05). However, playing football in an age category higher than their own was associated with significantly more active primitive reflexes (PR) compared to being in their age category ( p < 0.01). The results showed that 72.7% of “upgraded” football players had low GS and 18.2% had medium GS, compared to 55.3% and 2.1% in the non-upgraded group. Discussion The findings of the current study demonstrate that PR could still be active in a healthy population of high-level football players. Practicing a single sport for years and upgrading players could create a negative environment that can ultimately lead to the activation of otherwise integrated PR.
This study aimed to determine if concurrent endurance and strength training that matches the global running pattern would be more effective in increasing running economy (RE) than non-matched ...training. The global running pattern of 37 recreational runners was determined using the Volodalen
method as being aerial (AER) or terrestrial (TER). Strength training consisted of endurance running training and either plyometric (PLY) or dynamic weight training (DWT). Runners were randomly assigned to a matched (
= 18; DWT for TER, PLY for AER) or non-matched (
= 19; DWT for AER, PLY for TER) 8 weeks concurrent training program. RE, maximal oxygen uptake V̇O
max) and peak treadmill speed at V̇O
max (PTS) were measured before and after the training intervention. None of the tested performance related variables depicted a significant group effect or interaction effect between training and grouping (
≥ 0.436). However, a significant increase in RE, V̇O
max, and PTS (
≤ 0.003) was found after the training intervention. No difference in number of responders between matched and non-matched groups was observed for any of the performance related variables (
≥ 0.248). In recreational runners, prescribing PLT or DWT according to the global running pattern of individuals, in addition to endurance training, did not lead to greater improvements in RE.
Duty factor (DF) and step frequency (SF) were previously defined as the key running pattern determinants. Hence, this study aimed to investigate the association of DF and SF on 1) the vertical and ...fore-aft ground reaction force signals using statistical parametric mapping; 2) the force related variables (peaks, loading rates, impulses); and 3) the spring-mass characteristics of the lower limb, assessed by computing the force-length relationship and leg stiffness, for treadmill runs at several endurance running speeds. One hundred and fifteen runners ran at 9, 11, and 13 km/h. Force data (1000 Hz) and whole-body three-dimensional kinematics (200 Hz) were acquired by an instrumented treadmill and optoelectronic system, respectively. Both lower DF and SF led to larger vertical and fore-aft ground reaction force fluctuations, but to a lower extent for SF than for DF. Besides, the linearity of the force-length relationship during the leg compression decreased with increasing DF or with decreasing SF but did not change during the leg decompression. These findings showed that the lower the DF and the higher the SF, the more the runner relies on the optimization of the spring-mass model, whereas the higher the DF and the lower the SF, the more the runner promotes forward propulsion.
The aim was to identify the differences in lower limb kinematics used by high (DFhigh) and low (DFlow) duty factor (DF) runners, particularly their sagittal plane (hip, knee, and ankle) joint angles ...and pelvis and foot segment angles during stance. Fifty-nine runners were divided in two DF groups based on their mean DF measured across a range of speeds. Temporal characteristics and whole-body three-dimensional kinematics of the running step were recorded from treadmill runs at 8, 10, 12, 14, 16, and 18 km/h. Across speeds, DFhigh runners, which limit vertical displacement of the COM and promote forward propulsion, exhibited more lower limb flexion than DFlow during the ground contact time and were rearfoot strikers. On the contrary, DFlow runners used a more extended lower limb than DFhigh due to a stiffer leg and were midfoot and forefoot strikers. Therefore, two different lower limb kinematic mechanisms are involved in running and the one of an individual is reflected by the DF.
There is considerable inter-individual variability in self-selected intensity or running speed. Metabolic cost per distance has been recognized as a determinant of this personal choice. As ...biomechanical parameters have been connected to metabolic cost, and as different running patterns exist, we can question their possible determinant roles in self-selected speed. We examined the self-selected speed of 15 terrestrial and 16 aerial runners, with comparable characteristics, on a 400 m track and assessed biomechanical parameters and ratings of pleasure/displeasure. The results revealed that aerial runners choose greater speeds associated with shorter contact time, longer flight time, and higher leg stiffness than terrestrial runners. Pleasure was negatively correlated with contact time and positively with leg stiffness in aerial runners and was negatively correlated with flight time in terrestrial runners. We propose the existence of an optimization system allowing the connection of running patterns at running speeds, and feelings of pleasure or displeasure.
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