A lower duty factor (DF) reflects a greater relative contribution of leg swing versus ground contact time during the running step. Increasing time on the ground has been reported in the scientific literature to both increase and decrease the energy cost (EC) of running, with DF reported to be highly variable in runners. As increasing running speed aligns running kinematics more closely with spring-mass model behaviours and re-use of elastic energy, we compared the centre of mass (COM) displacement and EC between runners with a low (DF low ) and high (DF high ) duty factor at typical endurance running speeds. Forty well-trained runners were divided in two groups based on their mean DF measured across a range of speeds. EC was measured from 4 min treadmill runs at 10, 12 and 14 km h −1 using indirect calorimetry. Temporal characteristics and COM displacement data of the running step were recorded from 30 s treadmill runs at 10, 12, 14, 16 and 18 km h −1 . Across speeds, DF low exhibited more symmetrical patterns between braking and propulsion phases in terms of time and vertical COM displacement than DF high . DF high limited global vertical COM displacements in favour of horizontal progression during ground contact. Despite these running kinematics differences, no significant difference in EC was observed between groups. Therefore, both DF strategies seem energetically efficient at endurance running speeds.

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.

Close to 90% of recreational runners rearfoot strike in a long-distance road race. This prevalence has been obtained from North American cohorts of runners. The prevalence of rearfoot strikers has not been extensively examined in an Asian population of recreational runners. Therefore, the aim of this study was to determine the prevalence of rearfoot, midfoot, and forefoot strikers during a long-distance road race in Asian recreational runners and compare this prevalence to reported values in the scientific literature. To do so, we classified the foot strike pattern of 950 recreational runners at the 10 km mark of the Singapore marathon (77% Asian field). We observed 71.1%, 16.6%, 1.7%, and 10.6% of rearfoot, midfoot, forefoot, and asymmetric strikers, respectively. Chi-squared tests revealed significant differences between our foot strike pattern distribution and those reported from North American cohorts (P < 0.001). Our foot strike pattern distribution was similar to one reported from elite half-marathon runners racing in Japan (Fisher exact test, P = 0.168). We conclude that the prevalence of rearfoot strikers is lower in Asian than North American recreational runners. Running research should consider and report ethnicity of participants given that ethnicity can potentially explain biomechanical differences in running patterns.

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.

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How this prevalence changes throughout the course of a marathon remains undocumented. We filmed 350 runners at the 10 km and 39 km marks of the Singapore marathon ($71% Asian field), and classified footstrike patterns in 347 and 327 runners at these locations. The prevalence of rearfoot, midfoot, forefoot, and asymmetric patterns was 65%, 21%, 33%, and 11% at 10 km, which differed significantly from the corresponding 77%, 15%, 1%, and 8% at 39 km (p < 0.01). The prevalence of non-rearfoot strikers at both filming locations was greater than reported in the literature for North American recreational marathoners (p < 0.01), but lower than reported for non-Asian elite marathoners (p 0.02). The 12% increase in rearfoot strikers at the later mark of the marathon in our Asian cohort of recreational runners was greater than the 5% increase reported for the North American-based cohort (p < 0.01), but comparable to the one reported for non-Asian elite runners (p ¼ 0.97). Our findings confirm previous conclusions that running research should consider and report ethnicity alongside performance standards given that both can (in part) explain biomechanical differences in running gait. Noteworthy is that numerous factors can influence marathon performance and fatigue that here remained unaccounted for, including age, sex, course profile, footwear, and environmental conditions.

Runners were classified using two different methods based on their spontaneous running form: (1) subjectively using the V®score from the Volodalen® scale, leading to terrestrial and aerial groups; and (2) objectively using the duty factor (DF), leading to high (DFhigh) and low (DFlow) DF groups. This study aimed to compare these two classification schemes. Eighty-nine runners were divided in two groups using the V®score (VOL groups) and were also ranked according to their DF. They ran on a treadmill at 12 km·h−1 with simultaneous recording of running kinematics, using a three-dimensional motion capture system. DF was computed from data as the ratio of ground contact time to stride time. The agreement (95% confidence interval) between VOL and DF groups was 79.8% (69.9%, 87.6%), with relatively high sensitivity (81.6% (68.0%, 91.2%)) and specificity (77.5% (61.6%, 89.2%)). Our results suggest that the DF and V®score reflect similar constructs and lead to similar subgroupings of spontaneous running form (aerial runners if DF < 27.6% and terrestrial runners if DF > 28.8% at 12 km·h−1). These results suggest that DF could be a useful objective measure to monitor real-time changes in spontaneous running form using wearable technology. As a forward-looking statement, spontaneous changes in running form during racing or training could assist in identifying fatigue or changes in environmental conditions, allowing for a better understanding of runners.