How does running technique change with running speed? A quantitative analysis based on practice-informed principal components
Authors: Debertin Daniel , Jaén-Carrillo Diego , Roche Seruendo Luis Enrique , Federolf Peter 
Published: September 2024

Introduction & Purpose
“Running technique is an important component of running economy and performance” (Folland et al., 2017). While economy and performance can directly be measured, no common measuring method exists for running technique. The aims of this study were twofold: (I) develop practice-informed running technique measures based on technique characterizations used by coaches (i.e. distinct variations of body segment movements instead of discrete kinematics); (II) investigate, how running technique changes with running speed.
Methods
Two independent kinematic data sets were recorded on a treadmill using a retro-reflective marker setup (“Plugin-Gait”) and a 10-camera system (Vicon Motion Systems Ltd., Oxford, UK). First, 20 experienced runners (age 25 ± 2 y; 10 females, 10 males) were tasked to vary their running according to 14 technique elements (vertical, horizontal, hip and upper body movement, foot strike, track width, ankle rotation, leg swing, back posture, elbow flexion/extension, arm swing amplitude and direction, gaze direction, cadence) into two opposing extreme forms per element. Measures for the 14 running technique elements were developed using principal component analyses (one PCA per two opposing technique element variations) and selecting principal components (PCs; Federolf, 2016) that aligned with the represented technique element. Second, an additional 19 experienced runners (age 30 ± 9 y, 3 females, 16 males) ran at different speeds (10-17 km/h with 1 km/h incremental steps) without any technique instructions. Their data were projected onto the selected PCs, resulting in averaged PC score waveforms of the different speeds along each technique element. Waveforms were analysed using statistical parametric mapping (SPM) with a repeated measures ANOVA design (Pataky et al., 2013).
Results
For all 14 technique elements, sections of significant differences between at least two different speeds were found within the cycle-normalized PC score waveforms. Figure 1 exemplifies the results for the foot track width, where the lateral range of motion of the feet decreased with speed. Post-hoc analyses revealed further differences, such as less vertical and greater horizontal movement, as well as smaller leg swing and greater arm swing amplitude at 17 km/h compared to 10 km/h.
Discussion
Firstly, practice-informed and data-driven running technique measures could be developed (I). Secondly, the measures could be applied on a group of runners and plausible changes in their technique due to running speed were identified (II). So far, the speed-dependent technique adaptations only reflect the specific techniques on a treadmill for a predominately male reference group, but the presented concept can be transferred to other runners and settings.
Conclusion
Running technique varies with speed, and the developed technique measures facilitate comparisons of these differences using practically relevant technique elements. Since the movement adaptations associated with running speed are directly quantifiable and visualizable, technique models for different speed ranges might be developed by researchers and then utilized by runners to train and assess their technique in alignment with these models.
References
Folland, J. P., Allen, S. J., Black, M. I., Handsaker, J. C., & Forrester, S. E. (2017). Running technique is an important component of running economy and performance. Medicine & Science in Sports & Exercise, 49(7), 1412-1423. https://doi.org/10.1249%2FMSS.0000000000001245
Federolf, P. A. (2016). A novel approach to study human posture control: “Principal movements” obtained from a principal component analysis of kinematic marker data. Journal of Biomechanics, 49(3), 364-370. https://doi.org/10.1016/j.jbiomech.2015.12.030
Pataky, T. C., Robinson, M. A., & Vanrenterghem, J. (2013). Vector field statistical analysis of kinematic and force trajectories. Journal of Biomechanics, 46(14), 2394-2401. https://doi.org/10.1016/j.jbiomech.2013.07.031