The objective of this study was to establish the separate associations between parasympathetic modulations of the heart [evaluated through heart rate (HR) variability (HRV) indexes and postexercise HR recovery (HRR) indexes] with cardiorespiratory fitness and training load. We have measured cardiorespiratory fitness through peak oxygen consumption (Vo2 max) and estimated weekly training load with the Baecke sport score in 55 middle-aged individuals (30.8 +/- 1.8 yr, body mass index 24.5 +/- 0.4 kg/m2). HRV indexes were analyzed at rest under controlled breathing, and HRR was estimated from HR curve fitting after maximal exercise or from measurements of the number of beats recovered at 60 s after exercise. Multiple linear regressions were used to investigate the separate relationships between vagal-related HRV indexes and Vo2 max and Baecke scores. On the basis of their Vo2 max and Baecke scores, subjects were classified as fit or unfit and as low trained (LT) or moderately trained (MT), which yielded four groups: UnfitLT, UnfitMT, FitLT, and FitMT. Vagal-related HRV indexes were positively correlated with Vo2 max (P < 0.05) but not with Baecke scores. In contrast, HRR indexes were related to Baecke scores (P < 0.05) but not with Vo2 max. FitLT and FitMT had significantly higher (P < 0.05) normalized vagal-related HRV indexes than UnfitLT and UnfitMT, but HRR did not change. Moderate training was associated with significantly lower HRR indexes both in UnfitMT and FitMT compared with UnfitLT and FitLT, but there was no difference in vagal-related HRV indexes. These results indicate that vagal-related HRV indexes are related more to cardiorespiratory fitness, whereas HRR appears to be better associated with training load.

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.

Biomechanical parameters are often analyzed independently, although running gait is a dynamic system wherein changes in one parameter are likely to affect another. Accordingly, the Volodalen® method provides a model for classifying running patterns into 2 categories, aerial and terrestrial, using a global subjective rating scoring system. We aimed to validate the Volodalen® method by verifying whether the aerial and terrestrial patterns, defined subjectively by a running coach, were associated with distinct objectively-measured biomechanical parameters. The running patterns of 91 individuals were assessed subjectively using the Volodalen® method by an expert running coach during a 10-min running warm-up. Biomechanical parameters were measured objectively using the OptojumpNext® during a 50-m run performed at 3.3, 4.2, and 5 m·s(-1) and were compared between aerial- and terrestrial-classified subjects. Longer contact times and greater leg compression were observed in the terrestrial compared to the aerial runners. The aerial runners exhibited longer flight time, greater center of mass displacement, maximum vertical force and leg stiffness than the terrestrial ones. The subjective categorization of running patterns was associated with distinct objectively-quantified biomechanical parameters. Our results suggest that a subjective holistic assessment of running patterns provides insight into the biomechanics of running gaits of individuals.

Accelerometer-based systems are often used to quantify human movement. This study's aim was to assess the reliability and validity of the Myotest® accelerometer-based system for measuring running stride kinematics. Twenty habitual runners ran two 60 m trials at 12, 15, 18 and 21 km·h(-1). Contact time, aerial time and step frequency parameters from six consecutive running steps of each trial were extracted using Myotest® data. Between-trial reproducibility of measures was determined by comparing kinematic parameters from the two runs performed at the same speed. Myotest® measures were compared against photocell-based (Optojump Next®) and high-frequency video data to establish concurrent validity. The Myotest®-derived parameters were highly reproducible between trials at all running speeds (intra-class correlation coefficient (ICC): 0.886 to 0.974). Compared to the photo-cell and high-speed video-based measures, the mean contact times from the Myotest® were 34% shorter and aerial times were 64% longer. Only step frequency was comparable between systems and demonstrated high between-system correlation (ICC ≥ 0.857). The Myotest® is a practical portable device that is reliable for measuring contact time, aerial time and step frequency during running. In terms of validity, it provides accurate step frequency measures but underestimates contact time and overestimates aerial time compared to photocell- and optical-based systems.

Different running patterns were associated with similar RE. Aerial runners appear to rely more on elastic energy utilization with a rapid eccentric-concentric coupling time, whereas terrestrial runners appear to propel the body more forward rather than upward to limit work against gravity. Excluding runners with a mixed running pattern from analyses did not affect study interpretation.

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.

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.

Running patterns are often categorized into subgroups according to common features before data analysis and interpretation. The Volodalen method is a simple field-based tool used to classify runners into aerial or terrestrial using a 5-item subjective rating scale. We aimed to validate the Volodalen method by quantifying the relationship between its subjective scores and 3D biomechanical measures. Fifty-four runners ran 30 s on a treadmill at 10, 12, 14, 16, and 18 km h while their kinematics were assessed subjectively using the Volodalen method and objectively using 3D motion capture. For each runner and speed, two researchers scored the five Volodalen items on a 1-to-5 scale, which addressed vertical oscillation, upper-body motion, pelvis and foot position at ground contact, and footstrike pattern. Seven 3D biomechanical parameters reflecting the subjective items were also collected and correlated to the subjective scores. Twenty-eight runners were classified as aerial and 26 as terrestrial. Runner classification did not change with speed, but the relative contribution of the biomechanical parameters to the subjective classification was speed dependent. The magnitude of correlations between subjective and objective measures ranged from trivial to very large. Five of the seven objective parameters significantly differed between aerial and terrestrial runners, and these parameters demonstrated the strongest correlations to the subjective scores. Our results support the validity of the Volodalen method, whereby the visual appreciation of running gait reflected quantifiable objective parameters. Two minor modifications to the method are proposed to simplify its use and improve agreement between subjective and objective measures.