Foot strike pattern and impact continuous measurements during a trail running race: proof of concept in a world-class athlete

Abstract

Foot strike identification has become an important topic since it may be related to injury risk and performance. Due to step variability and the influence of environmental features on running biomechanics, it is relevant to assess as many steps as possible in field conditions. Our purpose was to apply a novel simple method to assess foot strike and impact from continuous acceleration measurements over a 45 km trail running race. Three wireless tridimensional accelerometers were set on the left tibia and shoe (at the heel and metatarsals) of the current best ultratrail runner. Vertical, antero-posterior and resultant peak tibial accelerations and median frequencies were measured. Step frequency (SF) was calculated from tibial acceleration. Foot strike was quantified from the time between heel and metatarsal peak accelerations (THM). Foot strike classification was performed according to THM criteria and expressed in percentages of rearfoot, midfoot and forefoot steps. Multiple linear regressions were computed to assess relationships between the impact magnitude and slope, SF and THM. Over the first 20 km, 5530 steps were analysed. The pattern classification revealed on average 18.5% of rearfoot strike, 32.6% of midfoot strike and 48.9% of forefoot strike over the ∼82 min analysed in the runner studied. The impact magnitude for him may be related to slope, also taking into account speed, SF and landing technique. The main findings of this study were that (1) portable accelerometers make possible the assessment of foot strike and shock acceleration in situ, (2) the antero-posterior and resultant components of tibial acceleration should not be neglected in the measurement of stress severity, and (3) the trail running world champion presents an atypical foot strike profile.

Keywords:

• accelerometers
• running pattern
• impact
• trail running
• entire race

Acknowledgements

We warmly thank the runner for his availability, and Jérémy Rossi (University of Savoie, France) for his valuable help on the data analysis.

Disclosure statement

We declare that we have no conflict of interest.

Additional information

Funding

This study was funded by Amer Sports Footwear.