A public dataset of running biomechanics and the effects of running speed on lower extremity kinematics and kinetics

Abstract

Background. The goals of this study were (1) to present the set of data evaluating running biomechanics (kinematics and kinetics), including data on running habits, demographics, and levels of muscle strength and flexibility made available at Figshare (DOI: 10.6084/m9.figshare.4543435); and (2) to examine the effect of running speed on selected gait-biomechanics variables related to both running injuries and running economy. Methods. The lower-extremity kinematics and kinetics data of 28 regular runners were collected using a three-dimensional (3D) motion-capture system and an instrumented treadmill while the subjects ran at 2.5 m/s, 3.5 m/s, and 4.5 m/s wearing standard neutral shoes. Results. A dataset comprising raw and processed kinematics and kinetics signals pertaining to this experiment is available in various file formats. In addition, a file of metadata, including demographics, running characteristics, foot-strike patterns, and muscle strength and flexibility measurements is provided. Overall, there was an effect of running speed on most of the gait-biomechanics variables selected for this study. However, the foot-strike patterns were not affected by running speed. Discussion. Several applications of this dataset can be anticipated, including testing new methods of data reduction and variable selection; for educational purposes; and answering specific research questions. This last application was exemplified in the study's second objective.

The stiff plate location into the shoe influences the running biomechanics

“…It was expected that the effects of the stiff plate location on running biomechanics would depend on the running speed, due to the differences in terms of loadings and lower limb biomechanics between the slower and the faster speed. The running speed difference (slower: 3.28 ± 0.28 m/s; faster: 4.01 ± 0.27 m/s) was indeed enough to induce significant changes as previously observed (Arampatzis, Brüggemann, & Metzler, 1999;Fukuchi, Fukuchi, & Duarte, 2017), that is: the faster speed increased vertical and propulsive GRF, increased hip joint range of motion, and increased net torques and work in all lower limb joints compared to the slower speed. The lack of significant interaction effect on running biomechanics suggested that adding a stiff plate into the shoe did not require specific location among speeds performed in the present study, which mainly corresponded to speeds performed by recreational runners (Gordon et al, 2017).…”

Positive Work Contribution Shifts from Distal to Proximal Joints during a Prolonged Run

“…It is surprising that most reports investigating exhausting running have focused on CoM kinetics, although it is known that CoM work is the result of a complex interaction of the joint work done by individual muscles, especially at the lower extremity (20,21). A joint-specific view allows to describe the individual contributions of different muscle groups to the total work of the lower extremity (22)(23)(24).…”

Dryft: A Python and MATLAB package to correct drifting ground reaction force signals during treadmill running

“…To test the performance of this method, I added drift to a 30-second vertical GRF signal collected by an instrumented treadmill during running (Fukuchi, Fukuchi, & Duarte, 2017). Using dryft to reduce this vertical GRF signal's drift produced favorable results, as the average (± SD) force measured across the extracted aerial phases values was -0.01 N (± 0.09 N) for the corrected signal ( Figure 2).…”