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Coefficient of variations at each speed for the spatiotemporal and spring-mass characteristics of the elite and trained runners.
Source publication
Elite middle distance runners present as a unique population in which to explore biomechanical phenomena in relation to running speed, as their training and racing spans a broad spectrum of paces. However, there have been no comprehensive investigations of running mechanics across speeds within this population. Here, we used the spring-mass model o...
Citations
... Furthermore, lower limb position at foot contact has been investigated for its influence on injury and performance (16). A more perpendicular shank relative to the ground and closer contacts to the body's center of mass allows for greater running economy by decreasing the braking force at ground contact (16)(17)(18). A higher braking force decreases running performance and also increases risk of RRI (16,18). ...
... Additionally, other factors such as lower limb stiffness, ground reaction forces (GRF), and propulsion forces differ between runners and contribute to RRI and performance indicators (e.g., running speed and efficiency) (16,17). The summed action of the ankle, knee, and hip extensors [i.e., total support moment (TSM)] contribute to propulsion during running (19). ...
... Furthermore, faster runners can apply 1.26 times greater average force per body weight in less time on the ground compared with slower runners, Frontiers in Sports and Active Living achieving 1.8 times faster top speeds (43). Elite runners have greater vertical forces 0.16 BW higher, and more vertical shank angle at ground contact compared with sub-elite runners (17). Therefore, our findings suggest that manipulating shank position presents a viable target for gait modification that may influence both injury risk and running performance. ...
Introduction
Running related injuries (RRI) are common, but factors contributing to running performance and RRIs are not commonly compared between different types of runners.
Methods
We compared running biomechanics previously linked to RRIs and performance between 27 recreational and 35 collegiate runners. Participants completed 5 overground running trials with their dominant limb striking a force plate, while outfitted with standardised footwear and 3-dimensional motion capture markers.
Results
Post hoc comparisons revealed recreational runners had a larger vertical loading rate (194.5 vs. 111.5 BW/s, p < 0.001) and shank angle (6.80 vs. 2.09, p < 0.001) compared with the collegiate runners who demonstrated greater vertical impulse (0.349 vs. 0.233 BWs, p < 0.001), negative impulse (−0.022 vs. −0.013 BWs, p < 0.001), positive impulse (0.024 vs. 0.014 BWs, p < 0.001), and propulsive force (0.390 vs. 0.333 BW, p = 0.002). Adjusted for speed, collegiate runners demonstrated greater total support moment (TSM), plantar flexor moment, knee extensor moment, hip extensor moment, and had greater proportional plantar flexor moment contribution and less knee extensor moment contribution to the TSM compared with recreational runners. Unadjusted for speed, collegiate runners compared with recreational had greater TSM and plantar flexor moment but similar joint contributions to the TSM.
Discussion
Greater ankle joint contribution may be more efficient and allow for greater capacity to increase speed. Improving plantarflexor function during running provides a strategy to improve running speed among recreational runners. Moreover, differences in joint kinetics and ground reaction force characteristics suggests that recreational and collegiate runners may experience different types of RRI.
... We undertook this investigation to explore the concept of "spring-mass similarity" and spring-mass behavior as an assessment strategy for systemic gait characteristics in runners of differing performance capacities and footwear conditions. Elite distance runners are an appealing group in which to explore whether similarity or deviations from simple elastic systems (i.e., spring-mass behavior) differs between distinct populations or abilities, as the mechanical etiology of their high performance capacities and running economies have been suggested to be systemic in nature-i.e., multi-factorial interactions of a large number of variables (Cavanagh et al., 1977;Williams and Cavanagh, 1987;Burns et al., 2021a). Kenyan distance runners may be particularly enlightening to this end, as their performance capacities are uniquely prodigious (Tucker et al., 2015), and previous observations of their gait characteristics and musculotendinous behavior have suggested that they exploit elastic biomechanical mechanisms to efficiently store and return energy through stance and flight (Sano et al., 2013;Kunimasa et al., 2014;Sano et al., 2015;Santos-Concejero et al., 2017). ...
The dynamic complexity and individualization of running biomechanics has challenged the development of objective and comparative gait measures. Here, we present and explore several novel biomechanical metrics for running that are informed by a canonical inter-species gait template-the spring-mass model. The measures assess running mechanics systemically against the template via quantifying characteristics of a runner's kinetics relative to the energy-conserving elastic system-i.e., their "spring-mass similarity". Applying these metrics in a retrospective cohort investigation, we studied the overground kinetics of two heterogenous populations of runners in two footwear conditions: elite and recreational athletes in shod and barefoot conditions. Across all measures and within foot strike types, the elite runners exhibited mechanics that were more similar to those of the ideally elastic spring-mass template. The elite runners had more symmetric bounces, less discrepancy (i.e., greater coordination) between horizontal and vertical kinetic changes, and better fit to a spring-mass vertical ground reaction force time series. Barefoot running elicited greater kinetic coordination in the recreational runners. At a faster speed, the elites further improved their similarity to the template. Overall, the more economical elite group exhibited greater likeness to the linearly elastic, energy-conserving spring-mass system than their recreational counterparts. This study introduces novel biomechanical measures related to performance in distance running. More broadly, it provides new, approachable metrics for systemic quantification of gait biomechanics in runners across all demographics. These metrics may be applied to assess a runner's global biomechanical response to a variety of interventions, including training adaptations, rehabilitation programs, and footwear conditions.
... The mean ± SD of the number of strides used to analyze each stage was 90.1 ± 5.6. The number of steps employed for the analysis were more than the 32-64 steps recommended in other studies [31][32][33][34]; however, the fact the number of steps were required to compute CV and α is debatable. ...
... While the CV of CT for long-distance runners was consistent, the CV of CT for middle-distance runners presented a significantly large variability at lower intensities, as hypothesized. Since spatiotemporal variability is associated with skill and expertise [33], it was suggested that long-distance runners had acquired a stable strike pattern at lower intensities due to their high training volume [23]. Besides, it has also been reported that runners self-optimize CT to minimize metabolic cost and CT has a narrower optimal range of metabolic cost than step frequency, inducing changes to metabolic cost with only minor alterations to CT [46]. ...
Stride-to-stride variability and fluctuations in running have been widely investigated in relation to fatigue, injury, and other factors. However, no studies have examined the relationship of stride-to-stride variability and fluctuations with lactate threshold (LT), a well-known performance indicator for distance runners that represents the threshold at which fast-twitch muscle fibers are activated and the glycolytic system is hyperactivated. In this study, we examined a relationship between LT and stride-to-stride variability and fluctuations in trained middle- and long-distance runners (n = 33). All runners were asked to perform multistage graded exercise tests while wearing accelerometers on the upper surface of their shoes. The LT was determined by measuring blood lactate concentrations after each stage. Three gait parameters for each step were calculated based on the acceleration data: stride time (ST), ground contact time (CT), and peak acceleration (PA). The coefficient of variation (CV) and the long-range correlations (α) for each parameter were also calculated. The effects of the runner's group and the relative intensity for CV and α on gait parameters were evaluated using a two-way repeated measures analysis of variance. Although no significant effect was observed in the CV and α of ST, significant intensity main effects were observed for the CV and α of CT and PA. The lack of significant changes in ST might be the result of runners' adequate control of ST to minimize energy cost. All the parameters showing significant changes with increasing intensity decreased dramatically when they were close to LT. This might have been caused by an increase in physiological load near LT and be interpreted as a variation in motor control because of alternations in the mobilized muscle fibers and physiological changes around the LT. The α should be useful for non-invasive LT detection.
... 5 In middle-distance runners, spring-mass characteristics 6 discriminate between runners of differing abilities, with greater leg and vertical stiffnesses, lower duty factors, and steeper impact angles distinguishing elite from highly trained runners. 7 However, the demands of successful middle-distance racing are not satisfied by efficient running characteristics alone; the need to modulate and sustain speeds across a spectrum of paces and to execute fast sprint finishes are essential. 8 Given the complexity of the event's dynamics, the kinematic, spatiotemporal, and global mechanical characteristics that facilitate superior 1500 m racing are unclear. ...
... Runners achieve faster speeds by increasing step length at lower speeds, but shift to increasing step frequency to achieve their fastest speeds. 24 In both elite and highly trained middle-distance runners, Burns et al. 7 observed a predominantly linear relationship with speed between both step length and step frequency across submaximal running speeds. However, at the fastest observed speeds in each group (23-25 km/h in the elite and 21-23 km/h in the sub-elite), there was a distinct nonlinear shift, with a similar plateau in step length and a sharp increase in step frequency. ...
... However, at the fastest observed speeds in each group (23-25 km/h in the elite and 21-23 km/h in the sub-elite), there was a distinct nonlinear shift, with a similar plateau in step length and a sharp increase in step frequency. 7 As middle-distance runners race in the anaerobic speed domain with the finish necessarily being a maximal sprint, 8 the mechanical strategies exhibited here indicate that elite middle-distance runners compete at speeds above this mechanical shift. Whereas the spatiotemporal observations suggest some differences related to finishing position, the global characteristics were more discriminatory. ...
The aim of this study was to analyse key kinematic, spatiotemporal, and global mechanical characteristics in world-class middle-distance racing. Eight men were recorded halfway along the home straight on the second, third and final laps in the 2017 IAAF World Championship 1500m final. Video data (150 Hz) from three high-definition camcorders were digitised to calculate relevant variables, subsequently analysed in relation to running speed and finishing position. Better-placed finishers had greater hip extension at initial contact and through late stance, greater knee excursion throughout stance, and longer overstriding distances. Step length did not change with faster speeds as runners relied on increasing step frequency, but the highest-finishing athletes had longer contact phases and greater fluctuations in speed through the step cycle, which were related to higher normalised peak horizontal forces. The best athletes also had lower leg stiffnesses and vertical stiffnesses. The extended contact phase and greater compression could allow for more sustained force production, enabling better acceleration and maintenance of sprinting speed, indicating a trade-off between aerobic energetic efficiency and anaerobic power capacity. Coaches should note that these factors, as well as the best athletes' greater overstriding distances, show that elite 1500m runners might prioritise a technique that favours running speed over economy.
... DF, which describes the step time relative to the flight time, decreased with increasing speed in both groups in this study, and this finding is also in line with other published studies [8,44]. Furthermore, EXP showed an overall lower DF than NOV (10 km/h: 17.3% less; 15 km/h: 20.3% less); this indicates that EXP had a longer flight phase than NOV at a given stance time. ...
Running has become increasingly popular worldwide. Among runners, there exists a wide range of expertise levels. Investigating the differences between runners at two extreme levels, that is novices and experts, is crucial to understand the changes that occur as a result of multiple years of training. Vertical oscillation of center of mass (CoM), stride frequency normalized to the leg length, and duty factor, which describes the step time relative to the flight time, are key biomechan-ical parameters that have been shown to be closely related to the running economy and are used to characterize the running style. The variability characteristics of these parameters may reveal valuable information concerning the control of human locomotion. However, how the expertise level and running speed affect the variability of these key biomechanical parameters has not yet been investigated. The aim of this study was to analyze the effects of expertise level (novice vs. expert) and running speed (10 km/h vs. 15 km/h) on these parameters and their variability. It was hypothesized that expert runners would have lower vertical oscillation of CoM, normalized stride frequency, and duty factor and show less variability in these parameters. The parameters' variability was opera-tionalized by the coefficient of variation. The mean values and variability of these key biomechani-cal parameters according to expertise level and running speed were compared with rmANOVAs. The results showed that the experts had a lower duty factor and less variable vertical oscillation of CoM and normalized stride frequency, independently of the running speed. At a higher running speed, the variability of vertical oscillation of CoM was higher, whereas that of normalized stride frequency and duty factor did not change significantly. To the best of our knowledge, this is the first study analyzing the effects of expertise level and running speed on the variability of key biome-chanical parameters.
... Research has shown that non-linear shifts in gait parameters with the increase in speed possibly are related to a transition to a sprinting-like technique (Burns et al., 2021) at high speeds. To consider these non-linear transitions and to complement the selection of metrics through linear methods, we also conducted statistical analysis to investigate the differences between the 10 highest (HP) and 10 lowest (LP) performing participants according to MAS, sVT2, and D ref . ...
... These findings highlight the fact that lower µCTt was due to running technique and not just the speed. Similar findings of lower µDFt and µCTt have been reported in treadmill running for the comparison between elite and highly trained runners (Burns et al., 2021) for a speed range (10-24 kmh −1 ) and a . /fspor. . ...
... In contrast to CT and DF, mean vertical stiffness (µVSt) contributed positively to all three performance variables [β ǫ (0.90, 1.2)], and the fastest runners had a considerably higher µVSt than the slowest runners ( Figure 6). Similar results have been reported for comparisons between elite runners, well-trained runners, and other (non-runner) athletes during treadmill running (da Rosa et al., 2019;Moore et al., 2019;Burns et al., 2021). For a comparable propulsive force, a higher VS results in a lower vertical excursion of the center of mass (COM) and a lower mechanical energy loss due to vertical oscillations. ...
Running mechanics are modifiable with training and adopting an economical running technique can improve running economy and hence performance. While field measurement of running economy is cumbersome, running mechanics can be assessed accurately and conveniently using wearable inertial measurement units (IMUs). In this work, we extended this wearables-based approach to the Cooper test, by assessing the relative contribution of running biomechanics to the endurance performance. Furthermore, we explored different methods of estimating the distance covered in the Cooper test using a wearable global navigation satellite system (GNSS) receiver. Thirty-three runners (18 highly trained and 15 recreational) performed an incremental laboratory treadmill test to measure their maximum aerobic speed (MAS) and speed at the second ventilatory threshold (sVT2). They completed a 12-minute Cooper running test with foot-worm IMUs and a chest-worn GNSS-IMU on a running track 1–2 weeks later. Using the GNSS receiver, an accurate estimation of the 12-minute distance was obtained (accuracy of 16.5 m and precision of 1.1%). Using this distance, we showed a reliable estimation [R2 > 0.9, RMSE ϵ (0.07, 0.25) km/h] of the MAS and sVT2. Biomechanical metrics were extracted using validated algorithm and their association with endurance performance was estimated. Additionally, the high-/low-performance runners were compared using pairwise statistical testing. All performance variables, MAS, sVT2, and average speed during Cooper test, were predicted with an acceptable error (R2 ≥ 0.65, RMSE ≤ 1.80 kmh−1) using only the biomechanical metrics. The most relevant metrics were used to develop a biomechanical profile representing the running technique and its temporal evolution with acute fatigue, identifying different profiles for runners with highest and lowest endurance performance. This profile could potentially be used in standardized functional capacity measurements to improve personalization of training and rehabilitation programs.
... An important factor in running mechanics is leg stiffness (k leg ); increased stiffness in running is important in reusing the elastic energy stored during the early stance loading phase (Butler et al., 2003;Burns et al., 2021) and is thus associated with the better running economy (Barnes et al., 2014). Vertical stiffness of the whole body (k vert ) is also used as a global measure of stiffness, usually increasing with running speed whereas leg stiffness is more consistent (Brazier et al., 2019). ...
English Premier League soccer players run at multiple speeds throughout a game. The aim of this study was to assess how well the duty factor, a dimensionless ratio based on temporal variables, described running styles in professional soccer players. A total of 25 players ran on an instrumented treadmill at 12, 16, and 20 km/h. Spatiotemporal and ground reaction force data were recorded for 30 s at each speed; video data (500Hz) were collected to determine footstrike patterns. In addition to correlation analysis amongst the 25 players, two groups (both N = 9) of high and low duty factors were compared. The duty factor was negatively correlated with peak vertical force, center of mass (CM) vertical displacement, and leg stiffness (kleg) at all speeds (r ≥ −0.51, p ≤ 0.009). The low duty factor group had shorter contact times, longer flight times, higher peak vertical forces, greater CM vertical displacement, and higher kleg (p < 0.01). Among the high DF group players, eight were rearfoot strikers at all speeds, compared with three in the low group. The duty factor is an effective measure for categorizing soccer players as being on a continuum from terrestrial (high duty factor) to aerial (low duty factor) running styles, which we metaphorically refer to as “grizzlies” and “gazelles,” respectively. Because the duty factor distinguishes running style, there are implications for the training regimens of grizzlies and gazelles in soccer, and exercises to improve performance should be developed based on the biomechanical advantages of each spontaneous running style.
... We believe that we made a suitable 265 choice here. Regardless, separate analyses found that if the cluster cutoff was higher, resulting in 289 runners (Burns et al., 2021). Thus, there may be competing interests for high-level runners, while 290 injury prevention may be weighted more heavily in recreational runners. ...
Bone stress injuries (BSI) are overuse injuries that commonly occur in runners. BSI risk is multifactorial and not well understood. Unsupervised machine learning approaches can potentially elucidate risk factors for BSI by looking for groups of similar runners within a population that differ in BSI incidence. Here, a hierarchical clustering approach is used to identify groups of collegiate cross country runners (32 females, 21 males) based on healthy pre-season running (4.47 m/s) gait data which were aggregated and dimensionally reduced by principal component analysis. Five distinct groups were identified using the cluster tree. Visual inspection revealed clear differences between groups in kinematics and kinetics, and linear mixed effects models showed between-group differences in metrics potentially related to BSI risk. The groups also differed in BSI incidence during the subsequent academic year (Rand index = 0.49; adjusted Rand index = -0.02). Groups ranged from those including runners spending less time contacting the ground and generating higher peak ground reaction forces and joint moments to those including runners spending more time on the ground with lower loads. The former groups showed higher BSI incidence, indicating that short stance phases and high peak loads may be risk factors for BSI. Since ground contact duration may itself account for differences in peak loading metrics, we hypothesize that the percentage of time a runner is in contact with the ground may be a useful metric to include in machine learning models for predicting BSI risk.
... Changes in cadence can lead to reduced contact time, although this could affect the magnitude of forward impulse required to achieve fast running speeds (Weyand et al., 2010), or to a reduction of flight time, which in turn could affect the distance achieved during flight and thereby reduce step length. A shorter contact time is associated with faster running because it results in a smaller duty factor (the proportion of a leg's cycle time spent in contact) (Forrester and Townend, 2015), which manifests as a "bouncy" running style where high vertical stiffness aids performance (Burns et al., 2021;van Oeveren et al., 2021). Maintaining short contact times is a key determinant of maintaining performance during runs to exhaustion (Hayes and Caplan, 2014), and highlights the value of analyzing temporal variables as athletes sprint to the finish in 800 m racing. ...
... It was noticeable in Figure 1 that the top two finishers had the shortest flight times on lap 2, resulting from their higher cadences, and ultimately a key factor in their success. Although lower duty factors are associated with faster running, they did not decrease between laps because the decrease in contact time was effectively offset by the decrease in swing time (and therefore total step time) and shows that duty factor is relatively constant because elite-standard athletes have robust mechanisms to exploit the advantages of better spring-mass behavior (Burns et al., 2021). Regardless of how the 800 m is a middle-distance event that relies on predominantly aerobic energy metabolism, the final stages are more sprint-like in mechanical terms and demonstrate the value of developing sprinting form in training (Bushnell and Hunter, 2007). ...
The 800 m race challenges the aerobic and anaerobic energy systems, and athletes adopt a technique that allows for running efficiency as well as sprinting speeds. The aim of this novel study was to compare important kinematic variables between the two laps of the 2017 IAAF World Championships women's final. Video data (150 Hz) were collected of all eight finalists on both laps at a distance approximately 50 m from the finish line along the home straight. Running speed, step length, cadence, temporal variables, sagittal plane joint angles, and shank angle at initial contact were measured. Running speed was faster on lap 2 (p = 0.008) because of large increases in cadence (p = 0.012). These higher cadences resulted in large decreases in contact times (p = 0.031) and in flight times (p = 0.016) on lap 2. Greater knee flexion and ankle plantarflexion (p ≤ 0.039) at initial contact on lap 2 seemed partly responsible for shorter swing times (p = 0.016), and which accompanied a decrease in shank angle at initial contact from lap 1 (7 •) to a more vertical position on lap 2 (4 •) (p = 0.008). Coaches should note that the need for higher cadence, horizontal impulse production during shorter contact times, and the adoption of forefoot striking require strength and neural system training to allow for athletes to increase cadence during the sprint finish. Increasing cadence (and not step length) was the driving factor for faster finishing speeds in the women's 800 m.
Background
Running biomechanics is considered an important determinant of running economy (RE). However, studies examining associations between running biomechanics and RE report inconsistent findings.
Objective
The aim of this systematic review was to determine associations between running biomechanics and RE and explore potential causes of inconsistency.
Methods
Three databases were searched and monitored up to April 2023. Observational studies were included if they (i) examined associations between running biomechanics and RE, or (ii) compared running biomechanics between groups differing in RE, or (iii) compared RE between groups differing in running biomechanics during level, constant-speed, and submaximal running in healthy humans (18–65 years). Risk of bias was assessed using a modified tool for observational studies and considered in the results interpretation using GRADE. Meta-analyses were performed when two or more studies reported on the same outcome. Meta-regressions were used to explore heterogeneity with speed, coefficient of variation of height, mass, and age as continuous outcomes, and standardization of running shoes, oxygen versus energetic cost, and correction for resting oxygen or energy cost as categorical outcomes.
Results
Fifty-one studies (n = 1115 participants) were included. Most spatiotemporal outcomes showed trivial and non-significant associations with RE: contact time r = − 0.02 (95% confidence interval [CI] − 0.15 to 0.12); flight time r = 0.11 (− 0.09 to 0.32); stride time r = 0.01 (− 0.8 to 0.50); duty factor r = − 0.06 (− 0.18 to 0.06); stride length r = 0.12 (− 0.15 to 0.38), and swing time r = 0.12 (− 0.13 to 0.36). A higher cadence showed a small significant association with a lower oxygen/energy cost (r = − 0.20 [− 0.35 to − 0.05]). A smaller vertical displacement and higher vertical and leg stiffness showed significant moderate associations with lower oxygen/energy cost (r = 0.35, − 0.31, − 0.28, respectively). Ankle, knee, and hip angles at initial contact, midstance or toe-off as well as their range of motion, peak vertical ground reaction force, mechanical work variables, and electromyographic activation were not significantly associated with RE, although potentially relevant trends were observed for some outcomes.
Conclusions
Running biomechanics can explain 4–12% of the between-individual variation in RE when considered in isolation, with this magnitude potentially increasing when combining different variables. Implications for athletes, coaches, wearable technology, and researchers are discussed in the review.
Protocol registration
https://doi.org/10.17605/OSF.IO/293ND (OpenScience Framework).
